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Behavioral Health Service Utilization and Preferences of Older Adults Receiving Home-Based Aging Services
Behavioral Health Service Utilization and Preferences of Older Adults Receiving Home-Based Aging Services Amber M. Gum, Ph.D., Lindsay Iser, M.A., Andrew Petkus, M.A.
Objective: To examine use of behavioral health services, treatment preferences, and facilitators and barriers to service use in older adults receiving home-based services within the aging network. Design: Cross-sectional survey. Setting: Interviews were conducted in participants’ homes. Participants: One hundred forty-two clients receiving home-based aging services. Measurements: Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; Brief Symptom Inventory-18; Discrimination-Devaluation Scale; utilization of behavioral health services; and preferences, facilitators, and barriers for behavioral health services. Results: Use of psychotropic medication was high (54.2%), primarily received in primary care settings (58.8%), with a few visits a year (54.0%). Participants were more likely to be taking psychotropic medication if they were younger and white. Approximately one-third of participants on antidepressant or antianxiety medication still met criteria for an Axis I disorder. Twentyone participants (14.8%) reported receiving counseling within the past year, with a few visits or less a year for most (57.1%). Almost all were willing to see at least one professional (97.2%) and try prescribed medications or counseling (90.1%). The most common barriers to service use were practical: affordability (71.8%), difficulty traveling (62.7%), and lack of transportation (45.8%). Conclusions: Aging network clients receiving home-based services have ready access to psychotropic medications but receive very few specialty behavioral health services and medication monitoring visits. They are willing to use a variety of behavioral health services and perceive mainly practical barriers to using services. The aging network has significant potential to enhance access to service utilization; strategies for integrating behavioral health services in the aging network are discussed. (Am J Geriatr Psychiatry 2010; 18:491–501) Key Words: Service utilization, homebound, aging services, treatment preferences
T
he aging network in the United States is gaining attention as a critical service sector for reaching vulnerable older adults at high risk of behavioral
health problems. The aging network is a federally and state-funded system that provides various social services to help older adults live as independently as
Received January 9, 2009; revised June 22, 2009; accepted June 30, 2009. From the Department of Aging and Mental Health Disparities, Louis de la Parte Florida Mental Health Institute, University of South Florida, Tampa, FL (AMG, LI); and San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA (AP). Send correspondence and reprint requests to Amber M. Gum, Ph.D., 13301 Bruce B. Downs Boulevard, MHC 1400, Tampa, FL 33612. e-mail: [email protected] © 2010 American Association for Geriatric Psychiatry
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Behavioral Health Service Utilization and Treatment possible, serving more than 9 million older adults annually.1 Recently, an expert panel of researchers and community providers recommended dissemination of behavioral health interventions within the aging network.2 Despite its vast national infrastructure and these recommendations, very little research has been conducted regarding behavioral health needs, service utilization, and help-seeking factors in this population. This information would provide a necessary foundation for tailoring behavioral health services for the aging network. The limited research with aging service clients suggests that behavioral health issues are common. Morrow-Howell et al.3 followed 299 depressed aging network clients and 315 randomly selected nondepressed clients for a year. In a smaller cross-sectional study, Gum et al.4 interviewed 142 clients receiving home-based case management within the aging network. Both studies indicated high rates of depression, with rates of 6%3 and 11.9%4 for a depressive disorder and 25% with subthreshold symptoms.3 In the longitudinal study,3 most depressed clients were persistently (40%) or intermittently depressed (28%) throughout the year. Rates of anxiety disorders were similarly high in the cross-sectional study (11.7%; Ref. 4). Other studies of homebound and medically ill older adults find comparably high rates of depression and anxiety.5–7 Morrow-Howell et al.3 also presented findings regarding service utilization. Only 9% of depressed clients had seen a psychiatrist and 7% had seen a mental health specialist in the past 6 months. Nonetheless, clients were generally open to using behavioral health services, as ⬎90% agreed that people should seek help for emotional problems and 77% responded that family doctors could be a “great help with a mental or emotional problem.” Depressed clients were more likely than nondepressed clients to report barriers of traveling and believing their problem would improve on its own. These findings are consistent with other research in that very few older adults receive behavioral health services,8 although the vast majority report positive attitudes about these services.9 A number of barriers may contribute to the discrepancy between willingness to use services and actual utilization. Much of this research has been based on Andersen’s behavioral model,10 which identifies three categories of individual-level factors that influence utilization
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of health services: need, predisposing factors (e.g., age, racial/ethnic background, and attitudes), and enabling factors (e.g., financial resources, transportation, and other resources). One of the strongest predictors of utilization is the individual’s perception of need,11 which goes unrecognized by many older adults.4 Older adults are also more likely to use behavioral health services if they are white, younger, female, and of higher socioeconomic status.12,13 Related to attitudes, stigma is associated with low service use,14,15 and matching preferences may facilitate service use.16,17 At the healthcare system level, one approach that can improve access and outcomes is integrating behavioral health services into existing systems that serve older adults, as demonstrated in randomized trials in primary care18 –20 and home healthcare.21 Extending this research into the aging network is a natural progression, as recommended by the expert panel.2 However, before implementing these recommendations, additional information is needed regarding clients’ service utilization, treatment preferences, and facilitators and barriers. Furthermore, services will likely need to be adapted to the varied settings of the aging network, such as nutrition sites or home-based care. Specifically, clients receiving home-based services are a high priority for integrated services as they are homebound and at high risk of institutionalization,1 placing them at high risk of behavioral health issues.4,6 Therefore, the purpose of this study was to examine behavioral health service utilization, treatment preferences, and facilitators and barriers in older adults receiving home-based services within the aging network. This study involved planned data analyses from the cross-sectional study of aging service clients conducted by Gum et al.4 For the current analyses, it was hypothesized that participants would be more likely to report use of behavioral health services if they were white, female, more highly educated, had an Axis I disorder, greater distress, lower stigma, self-identified having a behavioral health problem, and were attempting to reduce their level of distress. It also was hypothesized that participants would be willing to use a variety of services and that the most common barriers would be practical (e.g., finances and transportation).
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Gum et al. Measures
METHODS Overview Details of the study methods are reported elsewhere.4 The design was cross-sectional, and data were derived from interviews with clients conducted by trained research interviewers and standardized assessments conducted by clients’ case managers. All study procedures were approved by the University of South Florida Institutional Review Board, and all participants provided written informed consent.
Participants Participants (N ⫽ 142) were recruited from aging network agencies in four counties in Florida. Clients were recruited by case managers to participate in the study during routine home visits. Clients were eligible to participate if they were receiving home-based case management from the agency, aged 60 years or older, speak English, able to complete the case manager’s assessment independently, and had no known dementia diagnosis (per self-report of client, family member, or case manager). As reported previously,4 among clients who allowed the researchers to contact them, the response rate was 61.5%. Predominant reasons for nonparticipation were refusal due to health problems and cognitive impairment. Participants were aged 74.7 years (standard deviation ⫽ 8.3) on average, female (79.6%), white (73.9%), or black (19.7%), with 2.8% Hispanic ethnicity. Most had a high school education or more (33.8% high school; 27.5% less than high school; 38.7% more than high school), and were widowed (44.0%; 14.8% married; 33.1% divorced or separated; and 7.7% never married). Most reported their health as poor (35.9%) or fair (36.6%; 21.8% good; 4.2% very good; and 1.4% excellent). Most participants had two or more activities of daily living limitations (64.8%; 21.1% with 0; and 14.1% with 1), and all participants had at least two instrumental activities of daily living limitations, with 88.0% having four or more instrumental activities of daily living limitations (4.2% with two; and 7.7% with three). More details about participants’ characteristics are reported in the prior report.4
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Demographics. Participants reported age, sex, race, ethnicity, years of education, and marital status. Monthly Income. Monthly income was derived from the standard annual assessment by the case manager. Indicators of Physical Health. Participants selfrated their health using a five-point scale (1 ⫽ poor; 5 ⫽ excellent). The number of chronic physical health conditions was derived from the case manager’s report. The following chronic physical health conditions were provided: cancer, diabetes, emphysema, heart problems, liver problems, stroke, Parkinson disease, allergies, asthma, bladder/kidney problems, high blood pressure, gall bladder problems, and thyroid problems. Number of nonpsychotropic medications used was derived from either a list provided by the participant or a brown bag medication review with the participant. Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition-Axis I (Structured Clinical Interview for DSM-III-R [SCID22]). The SCID is a structured diagnostic interview that was used to diagnose Axis I disorders according to the Diagnostic and Statistical Manual of Psychiatric Disorders-IV.23 To minimize participant burden, questions were asked only in reference to current functioning, and only the following sections were included: major depressive episode, dysthymia, alcohol and substance abuse disorders, anxiety, and adjustment disorders. Independent ratings by the first author revealed substantial agreement between interviewers.4 Brief Symptom Inventory-18 (BSI-1824). For each of the 18 items, participants rate how much they have been bothered by the symptom for the past 7 days using a five-point scale (0 ⫽ not at all; 4 ⫽ extremely). It includes three subscales (depression, anxiety, and somatic; range: 0 –24) and a total score (range: 0 –72). Higher scores indicate more distress. This measure has been validated with various community and medical samples.24 In this sample, Cronbach alphas were 0.87 for depression, 0.81 for anxiety, 0.69 for somatic, and 0.89 for the total. Modified Mini-Mental State Examination (3MS25). The 3MS is a modification of the Mini-Mental State Examination,26 with four additional questions about similarities and revised scoring (range: 0 –100). It has
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Behavioral Health Service Utilization and Treatment superior validity and reliability compared with the Mini-Mental State Examination.25,27 Discrimination-Devaluation Scale (DDS28). The Discrimination-Devaluation Scale is the most widely used scale to assess mental health stigma and has good reliability and validity.28 It includes 12 items, rated using a six-point Likert scale (1 ⫽ strongly agree; 6 ⫽ strongly disagree). Six items are reverse scored. Items are summed and divided by 12 to result in a score range of 0 – 6. Higher scores represent greater stigma. Cronbach alpha in this sample was 0.70. Self-Identified Behavioral Health Problem. Participants were asked, “In the last 12 months, have you had a serious personal, emotional, or mental problem?” (yes/no29,30). Readiness to Change. Participants were asked about their readiness or attempts at making changes to reduce stress: “Have you attempted to reduce the amount of stress or sadness in your daily life?”31 Utilization of Behavioral Health Services. The interviewer recorded a list of participants’ current medications based on lists provided by participants or brown bag review. Medications were categorized into psychotropic classes (antidepressant, antianxiety, cognitive, and antipsychotic) according to lists of medications approved by the Federal Drug Administration and commonly used for each purpose, according to Julien32 and WebMD (accessed February 2008). The interviewer presented participants with a list (verbally and written) of professionals (psychologist/therapist/ counselor, social worker/case manager, psychiatrist, doctor [nonpsychiatrist], nurse, religious leader, alternative medicine professional, volunteer, and other) and asked “Have you ever seen any of these professionals to help deal with stress or sadness?”. Detailed questions followed for professionals seen within the past 12 months regarding type of treatment (prescribed medication, over-thecounter medication, case management, and talk therapy), location (primary care, emergency room, medical clinic, mental health clinic, senior center, religious setting, home, telephone), and frequency of visits (once/year, a few times/year, once/month, once/week, and nearly every day). These data were used to derive variables of professionals seen, types of treatment received, and location and frequency of visits for prescribed medication or counseling.
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Treatment Preferences, Facilitators, and Barriers. Participants were asked: “In the future, if you have problems with feelings of stress or sadness, which of these professionals would you be willing to go to for help?”. The same list of professionals, treatment types (support group added), and locations (residential setting added and emergency room omitted) from the questions on past service utilization were presented, and participants were asked which treatments and locations they would be willing to use. For each option participants were willing to use, they were asked to rank their most preferred. To identify barriers, participants were asked: “If you were having a problem with stress or sadness, would any of the following reasons stop you from getting any of these kinds of help, or from getting as much help as you may need?”. and were presented with a list of barriers. They were next asked, “Of these reasons, which would be the main reason you would not get help, or as much help as you may need?” This variable represented the “most influential barrier.” Similarly, they were asked about facilitators: “Would any of the following reasons make it more likely that you would get any of these kinds of help?” and were presented with a list of facilitators and asked to identify the “most influential facilitator.” Facilitators and barriers are listed in Table 4; these questions have been used in large-scale surveys of behavioral health service utilization.33 Procedures Interviews were conducted in participants’ homes. All measures were administered orally by research interviewers who were required to have at least a Bachelor’s degree in a relevant discipline and who were closely trained and supervised by the principal investigator (AG, licensed psychologist). Training and supervision involved use of official SCID training videotapes and materials, role play, and in-person and audiotaped review by the principal investigator. The only variable assessed by the case manager was monthly income, derived from the case manager’s routine assessment. Data Analysis SPSS Version 15.0 and STATA Version 9.2 were used for all statistical analyses. First, to examine
Am J Geriatr Psychiatry 18:6, June 2010
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Gum et al. services received, frequencies were derived for professional, location, and frequency of visits for psychotropic medication or counseling. To examine numbers of participants with Axis I disorders receiving services, frequencies were compared for those with and without an Axis I disorder. To examine covariates of service use, demographic (age, education, gender, monthly income, race/ethnicity, and marital status), clinical (self-rated health, SCID Axis I disorder, BSI-18, and 3MS), and helpseeking variables (stigma, self-identified behavioral health problem, and readiness to change) were compared for those who were taking psychotropic medications versus those not taking psychotropic medications. Bivariate comparisons were made using t tests for continuous variables and 2 for categorical variables. A similar comparison was not conducted for counseling because a small number of participants had received counseling in the past year (N ⫽ 21), and all but two of these individuals also received psychotropic medication. To further examine independent associations with psychotropic medication use, a multivariate logistic regression analysis was conducted with the following covariates: age (60 –93 years), gender (0 ⫽ male, 1 ⫽ female), race/ethnicity (0 ⫽ minority, 1 ⫽ white), years of education (0 –21), Axis I disorder (0 ⫽ no, 1 ⫽ yes), 3MS (64 –100), stigma (22–72), self-identified behavioral health problem (0 ⫽ no, 1 ⫽ yes), and readiness to change (0 ⫽ no, 1 ⫽ yes). These covariates were selected based on past research and the study hypotheses. Alpha of p ⱕ0.05 was used to determine significance in the final multivariate model. Frequencies were calculated for future willingness (yes/no) and most preferred for each professional, treatment modality, and location, as well as for all facilitators and barriers. Future willingness, facilitators, and barriers were compared for whites and minorities using 2 because of differences observed by race/ethnicity for service use.
RESULTS Current Use of Behavioral Health Services Table 1 displays details regarding the use of psychotropic medications and counseling. More than
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TABLE 1.
Characteristics of Psychotropic Medications and Counseling Received (N ⴝ 142) Axis I Disorder N (Row %) N (%)
Participants taking medications (n ⫽ 77, 54.2%) Category Any Antidepressant Antianxiety Cognitive Antipsychotic Antidepressant and antianxiety Number of categories 0 1 2 3 Prescribing professional (N ⫽ 51) Nonpsychiatrist MD Nurse Psychiatrist Location (N ⫽ 51) Primary care Other medical clinic Mental health clinic Emergency room Home Frequency of visits with prescribing professional (N ⫽ 50) One time/year Few times/year One time/month One time/week Nearly every day Participants receiving counseling (n ⫽ 21, 14.8%) Any Professional Psychologist/counselor Social worker Psychiatrist Location Primary care Other medical clinic Mental health clinic Emergency room Home Frequency One time/year Few times/year One time/month One time/week Nearly every day
No Yes (n ⴝ 107) (n ⴝ 31)
77 (100.0) 54 (70.1) 52 (67.5) 2 (2.6) 8 (10.4) 29 (37.7)
53 (71.6) 37 (69.8) 32 (65.3) 1 (100.0) 5 (62.5) 16 (57.1)
21 (28.4) 16 (30.2) 17 (34.7) 0 3 (37.5) 12 (42.9)
65 (45.8) 44 (57.1) 27 (35.1) 6 (7.8)
54 (84.4) 34 (81.0) 16 (59.3) 3 (60.0)
10 (15.6) 8 (19.0) 11 (40.7) 2 (40.0)
41 (80.4) 2 (3.9) 16 (31.4)
23 (59.0) 1 (50.0) 9 (56.3)
16 (41.0) 1 (50.0) 7 (43.8)
30 (58.8) 9 (17.6) 15 (29.4) 1 (2.0) 4 (7.8)
16 (57.1) 12 (42.9) 6 (66.7) 3 (33.3) 7 (50.0) 7 (50.0) 1 (100.0) 0 3 (75.0) 1 (25.0)
6 (12.0) 27 (54.0) 12 (24.0) 3 (6.0) 2 (4.0)
2 (33.3) 4 (66.7 16 (59.3) 11 (40.7) 6 (60.0) 4 (40.0) 3 (100.0) 0 2 (100.0) 0
21 (100.0) 12 (57.1) 14 (66.7) 8 (57.1) 2 (9.5) 0 10 (47.6) 5 (50.0)
9 (42.9) 6 (42.9) 2 (100.0) 5 (50.0)
0 3 (14.3) 13 (61.9) 1 (4.8) 6 (28.6)
0 3 (100.0) 6 (46.2) 1 (100.0) 3 (50.0)
0 0 7 (53.8) 0 3 (50.0)
5 (23.8) 7 (33.3) 7 (33.3) 1 (4.8) 1 (4.8)
5 (100.0) 4 (57.1) 3 (42.9) 0 0
0 3 (42.9) 4 (57.1) 1 (100.0) 1 (100.0)
Notes: Of the total sample (N ⫽ 142), 77 (54.2%) were prescribed psychotropic medications per the interviewer’s medication review and 21 (14.8%) reported receipt of counseling. For medications, prescribing professional (N ⫽ 51), location where prescribing professional was seen (N ⫽ 51), and frequency of visits with prescribing professional (N ⫽ 50) have missing data because some of the 77 participants did not self-identify as taking psychotropic medications and therefore did not report this information. Some numbers may add up to more than the totals due to a small number of participants seeing multiple professionals. Four participants were missing data for Axis I disorder; therefore the rows may not add up to the overall total in some cases.
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Behavioral Health Service Utilization and Treatment half of the sample was using at least one prescribed psychotropic medication (N ⫽ 77; 54.2%). Of the 77 participants who had psychotropic medications recorded by the interviewer, only 51 reported taking a psychotropic medication. Therefore, prescribing professional, location, and frequency of visits are missing for 26 individuals. Among those 51 reporting taking psychotropic medications, most received their prescriptions from a nonpsychiatrist medical doctor (N ⫽ 41, 80.4%) in a primary care setting (N ⫽ 30, 58.8%), for a few visits a year (N ⫽ 27, 54.0%). The highest percentage were taking antidepressants (N ⫽ 54, 70.1%) or antianxiety medications (N ⫽ 52, 67.5%), with a third taking two or more categories of psychotropic medication (N ⫽ 33, 42.9%). Of those taking an antidepressant or antianxiety medication, approximately one-third continued to meet criteria for an Axis I disorder (N ⫽ 16, 30.2% and N ⫽ 17, 34.7%, respectively). Also shown in Table 1, 21 participants (14.8%) reported having received counseling within the past year. Counseling was delivered primarily by a psychologist or counselor (N ⫽ 14, 66.7%) or psychiatrist (N ⫽ 10, 47.6%) in a specialty mental health clinic (N ⫽ 13, 61.9%). The frequency of counseling received was extremely low, however, at only a few times a year or less for the majority (N ⫽ 12, 57.1%). Table 2 presents comparisons of demographic and clinical variables according to psychotropic medication use. Those taking psychotropic medications were younger and more likely to be white; be taking more nonpsychotropic medications, have more chronic health conditions, be diagnosed with an anxiety disorder; have greater somatic, anxiety, and overall symptoms on the BSI-18; self-identify having a behavioral health problem; and report attempting to change. Of those diagnosed with an Axis I disorder, two-thirds (N ⫽ 21, 67.7%) were taking a psychotropic medication. In the multivariate logistic regression (N ⫽ 136; four missing Axis I disorder, one missing stigma scale, and one missing self-identified problem), only age and race were independently associated with being prescribed psychotropic medication. Participants were more likely to use psychotropic medications if they were younger (odds ratio ⫽ 0.929, 95% confidence interval ⫽ 0.883– 0.977, z [1] ⫽ 8.227, p ⫽ 0.004) and white (odds ratio ⫽ 4.341, 95% confidence
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interval ⫽ 1.644 –11.464, z [1] ⫽ 8.782, p ⫽ 0.003). No other covariates were significant (all p ⬎ 0.05).
Treatment Preferences, Facilitators, and Barriers As shown in Table 3, participants were willing to utilize a variety of professionals, treatment modalities, and locations. Almost all were willing to see at least one professional (N ⫽ 138, 97.2%) and try prescribed medications or counseling (N ⫽ 128, 90.1%). The largest numbers of participants were willing to see their primary care physician (N ⫽ 103, 72.5%), psychologist/counselor (N ⫽ 96, 67.6%), or case manager (N ⫽ 87, 61.3%), with primary care physician (N ⫽ 36, 25.4%) as the most preferred professional. Nearly equal numbers were willing to try prescribed medication (N ⫽ 105, 73.9%), counseling (N ⫽ 102, 71.8%) or case management (N ⫽ 104, 73.2%), with prescribed medication (N ⫽ 49, 34.5%) or counseling (N ⫽ 36, 25.4%) as the most preferred treatment type. Most participants were willing to receive services in their homes (N ⫽ 109, 76.8%), doctor’s office (N ⫽ 103, 72.5%) or a mental health office (N ⫽ 89, 62.7%), with home (N ⫽ 42, 29.6%) or doctor’s office (N ⫽ 33, 23.2%) as the most preferred locations. Facilitators and barriers are presented in Table 4. The most common facilitators that increased participants’ likelihood of seeking help were symptoms too severe to handle (N ⫽ 114, 80.3%), encouragement from others (N ⫽ 102, 71.8%), and financial assistance (N ⫽ 102, 71.8%), with symptoms too severe to handle reported as the most influential facilitator by the largest number of participants (N ⫽ 49, 34.5%). The most common barriers were affordability (N ⫽ 102, 71.8%), difficulty traveling (N ⫽ 89, 62.7%), and lack of transportation (N ⫽ 65, 45.8%). Affordability was the single most influential barrier (N ⫽ 46, 32.4%). Given the differences in psychotropic medication use by race, we examined future willingness, facilitators, and barriers by race (white, minority) using Pearson 2 analyses and Fisher’s exact tests. None of the willingness or barrier variables were significant (all p ⬎0.05). Only one facilitator differed significantly, getting help with transportation, 2[1] 6.90, p ⫽ 0.009, which was identified by 80.6% of minorities and 55.9% of whites.
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Gum et al.
TABLE 2.
Psychotropic Medication Use by Demographic and Clinical Characteristics (N ⴝ 142)
Age in years, M (SD) Education in years, M (SD) Gender Male Female Monthly income in dollars, M (SD) Race White Black Hispanic Native American Asian Multiracial Marital status Married Separated/divorced Never married Widow/widower Self-rated health Poor Fair Good Very good/excellent Nonpsychotropic medications M (SD) Chronic medical conditions M (SD) Any SCID disorder Any depressive MDE Substance Anxiety Adjustment disorder-depression Adjustment disorder-anxiety Adjustment disorder-mixed BSI-18 somatic, M (SD) BSI-18 depression, M (SD) BSI-18 anxiety, M (SD) BSI-18 total, M (SD) 3MS, M (SD) Stigma scale, M (SD) Self-identified problem (yes) Attempted change (yes)
No Medication (n ⴝ 65), N (%) or M (SD)
Medication (n ⴝ 77), N (%) or M (SD)
t (df) or 2 (df)
p
77.58 (8.36) 12.03 (3.20)
72.31 (7.52) 12.51 (2.28)
3.96 (140) ⫺1.03 (140)
⬍0.01 0.30
13 (44.8) 52 (46.0) 1005.05 (543.41)
16 (55.2) 61 (54.0) 976.68 (493.92)
0.01 (1)
0.91
0.33 (140)
0.75 ⬍0.01
40 (38.1) 20 (71.4) 2 (50.0) 1 (100.0) 0 2 (66.7)
65 (61.9) 8 (28.6) 2 (50.0) 0 1 (100.0) 1 (33.3)
—
9 (42.9) 22 (46.8) 1 (9.1) 33 (52.4)
12 (57.1) 25 (53.2) 10 (90.9) 30 (47.6)
7.16 (3)
0.07
—
0.45
19 (37.3) 24 (46.2) 18 (58.1) 4 (50.0) 6.63 (4.28) 4.25 (2.11) 10 (32.3) 5 (29.4) 5 (31.3) 2 (66.7) 4 (23.5) 2 (40.0) 2 (40.0) 5 (71.4) 4.60 (3.93) 3.25 (4.30) 2.63 (3.23) 10.48 (8.84) 87.62 (8.61) 44.81 (9.47) 14 (31.8) 38 (39.2)
32 (62.7) 28 (53.8) 13 (41.9) 4 (50.0) 8.30 (4.54) 5.73 (2.82) 21 (67.7) 12 (70.6) 11 (68.8) 1 (33.3) 13 (76.5) 3 (60.0) 3 (60.0) 2 (28.6) 6.41 (4.83) 4.91 (5.84) 4.62 (5.19) 15.93 (13.88) 88.57 (8.53) 46.87 (9.16) 30 (68.2) 59 (60.8)
⫺2.24 (140) ⫺3.49 (140) 3.21 (1) 2.08 (1) 1.53 (1) — 4.07 (1) — — — ⫺2.41 (140) ⫺1.90 (140) ⫺2.69 (140) ⫺2.74 (140) ⫺0.66 (140) ⫺1.31 (139) 5.25 (1) 5.37 (1)
0.03 0.01 0.07 0.15 0.22 0.59 0.05 1.00 1.00 0.25 0.02 0.06 ⬍0.01 ⬍0.01 0.51 0.19 0.02 0.02
Notes: Four missing Axis I disorder, one missing stigma scale, and one missing self-identified problem. Pearson 2 statistics are reported, except for race, self-reported health, substance abuse disorder, and the adjustment disorder variables. For these variables, Fisher’s exact test statistics are reported due to some cells with expected values ⬍5. SD: standard deviation.
DISCUSSION Broadly, the study findings indicate that aging network clients receiving home-based services have ready access to psychotropic medications but receive very few specialty behavioral health services and medication monitoring visits. They are willing to use a variety of behavioral health services and perceive mainly practical barriers to using services. The use of
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prescribed medications was quite high (54.2%); ⬎70% of participants diagnosed with an Axis I depressive or anxiety disorder in the research interview were taking at least one psychotropic medication. This result suggests that providers recognized and were attempting to address clients’ behavioral health issues, although the finding that many clients taking medications (⬎30%) continued to meet diagnostic criteria suggests that usual care is insufficient. The quality and intensity of medication management re-
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Behavioral Health Service Utilization and Treatment
TABLE 3.
Future Treatment Preferences for Behavioral Health Services
Any professional Professional type Psychologist/counselor Social worker/case manager Psychiatrist Primary care physician Nurse Religious/spiritual leader Alternative medicine healer Volunteer Other Relative/friend Home health aide Alcoholics Anonymous Lay minister Treatment modality Prescribed medication Over-the-counter medication Psychotherapy/counseling Support group Case management Location Mental health office/clinic Doctor’s office Senior center Residential facility Religious/spiritual setting Home Telephone
Willing, N (%)
Most Preferred, N (%)
138 (97.2)
—
96 (67.6) 87 (61.3) 74 (52.1) 103 (72.5) 71 (50.0) 76 (53.5) 31 (21.8) 52 (36.6) 37 (26.1) 28 (19.7) 7 (4.9) 1 (0.7) 1 (0.7)
19 (13.4) 9 (6.3) 17 (12) 36 (25.4) 5 (3.5) 24 (16.9) 2 (1.4) 3 (2.1) 23 (16.2) — — — —
105 (73.9) 44 (31.0) 102 (71.8) 78 (54.9) 104 (73.2)
49 (34.5) 3 (2.1) 36 (25.4) 19 (13.4) 26 (18.3)
89 (62.7) 103 (72.5) 54 (38.0) 43 (30.3) 67 (47.2) 109 (76.8) 71 (50.0)
19 (13.4) 33 (23.2) 5 (3.5) 4 (2.8) 16 (11.3) 42 (29.6) 16 (11.3)
Notes: One missing for all variables; numbers for most preferred do not always add to 138 due to a small number of participants who refused to rank options they were willing to use. All percentages are based on the total sample, N ⫽ 142.
ceived may have contributed to clients’ persistence of symptoms. Almost all medications were received from nonpsychiatrists in nonspecialty settings, where quality of behavioral health services tends to be lower than in specialty settings.8 Although depressed older adults require ongoing medication monitoring and switching to achieve remission,34 most participants (66%) only saw the prescribing professional a few times per year. Use and intensity of counseling were also low. Although a sizable minority (14.8%) reported receipt of counseling within the past year, frequency of visits was extremely low (once a month or less for 90.5% of those receiving counseling). Almost all those receiving counseling were also taking medications. Participants may have labeled medication visits or occasional discussions with providers regarding their
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TABLE 4.
Facilitators and Barriers to Accessing Behavioral Health Services
Facilitators If my symptoms became too severe to handle If others encouraged me to seek help Getting help to pay for it Getting help with transportation Finding out where to go to get help Barriers I couldn’t afford the money It’s hard to travel to appointments I don’t have transportation I prefer to manage it myself I don’t want to take more medication I think it’s better to keep these matters private I think it would go away by itself I don’t know where to go to get help I would get help from another source My symptoms would interfere with seeking help I don’t think treatment would help The problem wouldn’t bother me I am concerned to ask or what others would think I don’t have time
Facilitator/ Barrier Identified (yes), N (%)
Most Influential Facilitator/ Barrier, N (%)
114 (80.3)
49 (34.5)
102 (71.8)
9 (6.3)
102 (71.8) 86 (60.6)
26 (18.3) 32 (22.5)
73 (51.4)
12 (8.5)
102 (71.8) 89 (62.7)
46 (32.4) 9 (6.3)
65 (45.8) 62 (43.7) 54 (38.0)
31 (21.8) 12 (8.5) 8 (5.6)
46 (32.4)
9 (6.3)
42 (29.6)
2 (1.4)
39 (27.5)
5 (3.5)
39 (27.5)
4 (2.8)
28 (19.7)
1 (0.7)
21 (14.8)
3 (2.1)
21 (14.8)
0
20 (14.1)
2 (1.4)
8 (5.6)
0
Notes: One to six responses missing across items. All percentages are based on the total sample, N ⫽ 142.
moods as “counseling” sessions. Thus, although clients may occasionally access providers for some type of discussion, receipt of counseling at a frequency comparable to evidence-based psychotherapy35 is extremely rare. Consistent with hypotheses, participants were open to a range of behavioral health services. More than 90% were willing to try either medication or counseling; indeed, more than half of participants were already taking some form of psychotropic medication. These findings are also consistent with other recent research9 and counters the assumption that
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Gum et al. older adults are not open to using behavioral health services. Relevant to the aging network, most clients were willing to discuss behavioral health issues with a case manager (61%) and receive case management for distress (73%). Home and primary care physicians’ offices were the locations in which most participants were open to receiving services. As expected, the most commonly reported barriers were practical: finances, difficulty traveling to appointments, and lack of transportation. Alternatively, the most common and influential facilitator was related to perceived need: if symptoms became “too severe to handle.” Unfortunately, it is not possible to determine each client’s definition of symptoms that are “too severe.” Our prior research with this sample suggest that older adults’ perceptions of their behavioral health problems are complex and not necessarily related to severity of symptoms; rather, perceptions were associated with their familiarity of behavioral health issues in other people.4 Enhancing affordability, access to transportation, and being encouraged by others to seek help were also common facilitators. Taken together, these findings suggest that most of the older adults are open to discussing distress they are experiencing and behavioral health services. Specifically, professionals may be able to facilitate service use by educating the older person about behavioral health problems, helping the person become familiar with symptoms and when treatment is indicated, and reducing practical barriers. Consistent communication between professionals and older adults pertaining to these areas may help reduce stigma and increase commitment to engage in behavioral health treatments. Findings suggest that case managers in the aging network can overcome a number of identified barriers to increase access to behavioral health services. They are well positioned to conduct in-home screening and symptom monitoring, similar to an effective screening and referral intervention implemented in home healthcare.21 Case managers can also provide psychoeducation that incorporates facilitators to service use such as information about symptom severity and encouraging service use. Moreover, case managers can increase access to counseling by integrating counseling with case management, a promising approach based on one study with low-income older adults36 and research with younger age groups.37 The findings also suggest that case managers need to work closely with primary care providers, given
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the high use of and preference for medications from primary care. Comprehensive case management in collaboration with primary care providers may facilitate clients’ ability to access primary care services, although case managers have reported challenges collaborating with primary care.38 This collaboration may also reduce the racial and ethnic disparity that was observed for medication use, given that research in primary care has demonstrated that depression care management can remove disparities in access for minority elders.39 Several limitations should be considered. The most important limitation concerns the generalizability of the sample, given the relatively small sample size and restricted geographical area. One particular threat to generalizability is the selection bias, as participants represent a convenience sample recruited by case managers. As reported previously,4 compared with the full caseload of clients in the same region of Florida, participants were slightly younger on average, less likely to be Hispanic, and slightly less limited in activities of daily livings. Thus, the findings likely do not generalize to the most frail clients and Hispanic clients. Receipt of psychotropic medications with appropriate monitoring and counseling are likely to be even lower for these groups of older adults than for the current sample, given the additional barriers to service use faced by especially frail elders with limited mobility and Hispanic clients who may not speak fluent English. Cognitive impairment is likely an additional complicating factor in service delivery for the frailest clients. If these hypotheses are correct, then case managers could play a particularly essential role in service delivery to these older adults, if they can communicate in Spanish and deliver services in clients’ homes. A second limitation is the lack of assessment of bipolar disorder; this section of the SCID was omitted to minimize participant burden, but the possibility of some participants identified with major depressive episodes actually having bipolar disorder cannot be ruled out. Third, details are not available regarding the quality of services provided, such as medication dosage or length of time on medications. Unfortunately, some of the participants who were identified as being prescribed psychotropic medications per medication review did not self-identify as taking such medications, resulting in missing data for additional details regarding the prescribing pro-
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Behavioral Health Service Utilization and Treatment fessional. Despite these limitations, we believe that the findings provide an important basis for beginning to implement behavioral health interventions in the aging network. Moreover, the validity of the findings is corroborated by other studies with older adults, which have also found low use of specialty services,8,9 high use of general medical services,40 high willingness to use services,9 and predominantly practical barriers to accessibility.3 Future research is needed to adapt behavioral interventions for the aging network to match clients’ needs and preferences and characteristics of the aging network. One promising avenue is the development of strategies to facilitate case managers’ collaboration with primary care to comprehensively manage clients’ depression and anxiety through screening, referral, and interventions delivered in home and primary care. Other potential areas of
inquiry include training case managers to conduct screening, make referrals, and encourage clients’ engagement in services. By utilizing the vast resources of the aging network, such as clients’ existing relationships with case managers who make home visits, the aging network has exceptional potential to reach vulnerable older adults, thereby enhancing access to services and behavioral health outcomes.
The authors thank the older adults who participated in this study and the aging service agencies that collaborated with us to complete this study: Community Aging and Retirement Services, Inc., Gulf Coast Jewish Family Services, Hillsborough County Aging Services, and Polk County Elderly Services. This work was supported by a grant from University of South Florida New Researcher (to AMG).
References 1. Administration on Aging: Modernizing Older Americans Act Programs, Washington, DC, U.S. Administration on Aging, 2006 2. Steinman LE, Frederick JT, Prohaska T, et al: Recommendations for treating depression in community-based older adults. Am J Prev Med 2007; 33:175–181 3. Morrow-Howell N, Proctor E, Choi S, et al: Depression in public community long-term care: implications for intervention development. J Behav Health Serv Res 2008; 35:37–51 4. Gum AM, Petkus A, McDougal SJ, et al: Behavioral health needs and problem recognition by older adults receiving home-based aging services. Int J Geriatr Psychiatry 2009; 24:400 – 408 5. Blazer DG: Depression in late life: review and commentary. J Gerontol A Biol Sci Med Sci 2003; 58:249 –265 6. Bruce ML, McAvay GJ, Raue PJ, et al: Major depression in elderly home health care patients. Am J Psychiatry 2002; 159:1367–1374 7. Lenze EJ, Rogers JC, Martire LM, et al: The association of late-life depression and anxiety with physical disability: a review of the literature and prospectus for future research. Am J Geriatr Psychiatry 2001; 9:113–135 8. Wang PS, Lane M, Olfson M, et al: Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Arch Gen Psychiatry 2005; 62: 629 – 640 9. Mackenzie CS, Scott T, Mather A, et al: Older adults’ help-seeking attitudes and treatment beliefs concerning mental health problems. Am J Geriatr Psychiatry 2008; 16:1010 –1019 10. Andersen RM: Revisiting the behavioral model and access to medical care: does it matter? J Health Soc Behav 1995; 36:1–10 11. Klap R, Unroe KT, Unu ¨ tzer J: Caring for mental illness in the United States: a focus on older adults. Am J Geriatr Psychiatry 2003; 11:517–524 12. Crystal S, Sambamoorthi U, Walkup JT, et al: Diagnosis and treatment of depression in the elderly medicare population: predictors, disparities, and trends. J Am Geriatr Soc 2003; 51:1718 –1728 13. Neighbors HW, Woodward AT, Bullard KM, et al: Mental health service use among older African Americans: the Na-
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tional Survey of American life. Am J Geriatr Psychiatry 2008; 16:948 –956 14. Ayalon L, Area´n PA, Alvidrez J: Adherence to antidepressant medications in Black and Latino elderly patients. Am J Geriatr Psychiatry 2005; 13:572–580 15. Sirey JA, Bruce ML, Alexopoulos GS, et al: Perceived stigma as a predictor of treatment discontinuation in young and older outpatients with depression. Am J Psychiatry 2001; 158: 479 – 481 16. Rokke PD, Tomhave JA, Jocic Z: The role of client choice and target selection in self-management therapy for depression in older adults. Psychol Aging 1999; 14:155–169 17. Thompson JD, Scott NA: Counseling service features: elders’ preferences and utilization. Clin Gerontol 1991; 11:39 – 46 18. Bartels SJ, Coakley EH, Zubritsky C, et al: Improving access to geriatric mental health services: a randomized trial comparing treatment engagement with integrated versus enhanced referral care for depression, anxiety, and at-risk alcohol use. Am J Psychiatry 2004; 161:1455–1462 19. Bruce ML, Ten Have TR, Reynolds CF III, et al: Reducing suicidal ideation and depressive symptoms in depressed older primary care patients: a randomized controlled trial. JAMA 2004; 291: 1081–1091 20. Unu ¨ tzer J, Katon W, Callahan CM, et al; IMPACT Investigators. Improving Mood-Promoting Access to Collaborative Treatment: Collaborative care management of late-life depression in the primary care setting: a randomized controlled trial. JAMA 2002; 288:2836 –2845 21. Bruce ML, Brown EL, Raue PJ, et al: A randomized trial of depression assessment intervention in home health care. J Am Geriatr Soc 2007; 55:1793–1800 22. First MB, Spitzer RL, Miriam G, et al: Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition With Psychotic Screen. New York, Biometrics Research, New York State Psychiatric Institute, 2002
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Gum et al. 23. American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, 4th ed. Washington, DC, American Psychiatric Association, 1994 24. Derogatis L: Brief Symptom Inventory (BSI) 18: Administration, Scoring, and Procedures Manual. Minneapolis, MN, National Computer Systems, 2000 25. Teng EL, Chui HC: The Modified Mini-Mental State Examination. J Clin Psychiatry 1987; 48:314 –318 26. Folstein MF, Folstein SE, McHugh PR: Mini-mental state: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12:189 –198 27. Teng EL, Chui HC: Manual for the Administration and Scoring of the Modified Mini-Mental State (3MS) Test. Los Angeles, CA, University of Southern California School of Medicine, 1991 28. Link BG, Cullen FT, Struening EL, et al: A modified labeling theory approach to mental disorders: an empirical assessment. Am Sociol Rev 1989; 54:400 – 423 29. Alvidrez J, Azocar F: Distressed women’s clinic patients: preferences for mental health treatments and perceived obstacles. Gen Hosp Psychiatry 1999; 21:340 –347 30. Jorm AF, Korten AE, Jacomb PA, et al: “Mental health literacy”: a survey of the public’s ability to recognise mental disorders and their beliefs about the effectiveness of treatment. Med J Aust 1997; 166:182–186 31. Nigg CR, Burbank P, Padula C, et al: Stages of change across ten health risk behaviors for older adults. Gerontologist 1999; 39:473–482 32. Julien RM: A Primer of Drug Action: A Comprehensive Guide to the Actions, Uses, and Side Effects of Psychoactive Drugs, 3rd ed. Portland, OR, Worth, 2005
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33. Thompson A, Hunt C, Issakidis C: Why wait? Reasons for delay and prompts to seek help for mental health problems in an Australian clinical sample. Soc Psychiatry Psychiatr Epidemiol 2004; 39:810 – 817 34. Al Jurdi RK, Marangell LB, Petersen NJ, et al: Prescription patterns of psychotropic medications in elderly compared with younger participants who achieved a “recovered” status in the systematic treatment enhancement program for bipolar disorder. Am J Geriatr Psychiatry 2008; 16:922–933 35. Area´n PA, Cook BL: Psychotherapy and combined psychotherapy/ pharmacotherapy for late life depression. Biol Psychiatry 2002; 52: 293–303 36. Area´n PA, Gum A, McCulloch CE, et al: Treatment of depression in low-income older adults. Psychol Aging 2005; 20:601– 609 37. Miranda J, Azocar F, Organista KC, et al: Treatment of depression among impoverished primary care patients from ethnic minority groups. Psychiatr Serv 2003; 54:219 –225 38. Munson M, Proctor E, Morrow-Howell N, et al: Case managers speak out: responding to depression in community long-term care. Psychiatr Serv 2007; 58:1124 –1127 39. Ayalon L, Area´n PA, Linkins K, et al: Integration of mental health services into primary care overcomes ethnic disparities in access to mental health services between black and white elderly. Am J Geriatr Psychiatry 2007; 15:906 –912 40. Uebelacker LA, Wang PS, Berglund P, et al: Clinical differences among patients treated for mental health problems in general medical and specialty mental health settings in the National Comorbidity Survey Replication. Gen Hosp Psychiatry 2006; 28:387–395
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Objective: To examine use of behavioral health services, treatment preferences, and facilitators and barriers to service use in older adults receiving home-based services within the aging network. Design: Cross-sectional survey. Setting: Interviews were conducted in participants’ homes. Participants: One hundred forty-two clients receiving home-based aging services. Measurements: Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; Brief Symptom Inventory-18; Discrimination-Devaluation Scale; utilization of behavioral health services; and preferences, facilitators, and barriers for behavioral health services. Results: Use of psychotropic medication was high (54.2%), primarily received in primary care settings (58.8%), with a few visits a year (54.0%). Participants were more likely to be taking psychotropic medication if they were younger and white. Approximately one-third of participants on antidepressant or antianxiety medication still met criteria for an Axis I disorder. Twentyone participants (14.8%) reported receiving counseling within the past year, with a few visits or less a year for most (57.1%). Almost all were willing to see at least one professional (97.2%) and try prescribed medications or counseling (90.1%). The most common barriers to service use were practical: affordability (71.8%), difficulty traveling (62.7%), and lack of transportation (45.8%). Conclusions: Aging network clients receiving home-based services have ready access to psychotropic medications but receive very few specialty behavioral health services and medication monitoring visits. They are willing to use a variety of behavioral health services and perceive mainly practical barriers to using services. The aging network has significant potential to enhance access to service utilization; strategies for integrating behavioral health services in the aging network are discussed. (Am J Geriatr Psychiatry 2010; 18:491–501) Key Words: Service utilization, homebound, aging services, treatment preferences
T
he aging network in the United States is gaining attention as a critical service sector for reaching vulnerable older adults at high risk of behavioral
health problems. The aging network is a federally and state-funded system that provides various social services to help older adults live as independently as
Received January 9, 2009; revised June 22, 2009; accepted June 30, 2009. From the Department of Aging and Mental Health Disparities, Louis de la Parte Florida Mental Health Institute, University of South Florida, Tampa, FL (AMG, LI); and San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA (AP). Send correspondence and reprint requests to Amber M. Gum, Ph.D., 13301 Bruce B. Downs Boulevard, MHC 1400, Tampa, FL 33612. e-mail: [email protected] © 2010 American Association for Geriatric Psychiatry
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Behavioral Health Service Utilization and Treatment possible, serving more than 9 million older adults annually.1 Recently, an expert panel of researchers and community providers recommended dissemination of behavioral health interventions within the aging network.2 Despite its vast national infrastructure and these recommendations, very little research has been conducted regarding behavioral health needs, service utilization, and help-seeking factors in this population. This information would provide a necessary foundation for tailoring behavioral health services for the aging network. The limited research with aging service clients suggests that behavioral health issues are common. Morrow-Howell et al.3 followed 299 depressed aging network clients and 315 randomly selected nondepressed clients for a year. In a smaller cross-sectional study, Gum et al.4 interviewed 142 clients receiving home-based case management within the aging network. Both studies indicated high rates of depression, with rates of 6%3 and 11.9%4 for a depressive disorder and 25% with subthreshold symptoms.3 In the longitudinal study,3 most depressed clients were persistently (40%) or intermittently depressed (28%) throughout the year. Rates of anxiety disorders were similarly high in the cross-sectional study (11.7%; Ref. 4). Other studies of homebound and medically ill older adults find comparably high rates of depression and anxiety.5–7 Morrow-Howell et al.3 also presented findings regarding service utilization. Only 9% of depressed clients had seen a psychiatrist and 7% had seen a mental health specialist in the past 6 months. Nonetheless, clients were generally open to using behavioral health services, as ⬎90% agreed that people should seek help for emotional problems and 77% responded that family doctors could be a “great help with a mental or emotional problem.” Depressed clients were more likely than nondepressed clients to report barriers of traveling and believing their problem would improve on its own. These findings are consistent with other research in that very few older adults receive behavioral health services,8 although the vast majority report positive attitudes about these services.9 A number of barriers may contribute to the discrepancy between willingness to use services and actual utilization. Much of this research has been based on Andersen’s behavioral model,10 which identifies three categories of individual-level factors that influence utilization
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of health services: need, predisposing factors (e.g., age, racial/ethnic background, and attitudes), and enabling factors (e.g., financial resources, transportation, and other resources). One of the strongest predictors of utilization is the individual’s perception of need,11 which goes unrecognized by many older adults.4 Older adults are also more likely to use behavioral health services if they are white, younger, female, and of higher socioeconomic status.12,13 Related to attitudes, stigma is associated with low service use,14,15 and matching preferences may facilitate service use.16,17 At the healthcare system level, one approach that can improve access and outcomes is integrating behavioral health services into existing systems that serve older adults, as demonstrated in randomized trials in primary care18 –20 and home healthcare.21 Extending this research into the aging network is a natural progression, as recommended by the expert panel.2 However, before implementing these recommendations, additional information is needed regarding clients’ service utilization, treatment preferences, and facilitators and barriers. Furthermore, services will likely need to be adapted to the varied settings of the aging network, such as nutrition sites or home-based care. Specifically, clients receiving home-based services are a high priority for integrated services as they are homebound and at high risk of institutionalization,1 placing them at high risk of behavioral health issues.4,6 Therefore, the purpose of this study was to examine behavioral health service utilization, treatment preferences, and facilitators and barriers in older adults receiving home-based services within the aging network. This study involved planned data analyses from the cross-sectional study of aging service clients conducted by Gum et al.4 For the current analyses, it was hypothesized that participants would be more likely to report use of behavioral health services if they were white, female, more highly educated, had an Axis I disorder, greater distress, lower stigma, self-identified having a behavioral health problem, and were attempting to reduce their level of distress. It also was hypothesized that participants would be willing to use a variety of services and that the most common barriers would be practical (e.g., finances and transportation).
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Gum et al. Measures
METHODS Overview Details of the study methods are reported elsewhere.4 The design was cross-sectional, and data were derived from interviews with clients conducted by trained research interviewers and standardized assessments conducted by clients’ case managers. All study procedures were approved by the University of South Florida Institutional Review Board, and all participants provided written informed consent.
Participants Participants (N ⫽ 142) were recruited from aging network agencies in four counties in Florida. Clients were recruited by case managers to participate in the study during routine home visits. Clients were eligible to participate if they were receiving home-based case management from the agency, aged 60 years or older, speak English, able to complete the case manager’s assessment independently, and had no known dementia diagnosis (per self-report of client, family member, or case manager). As reported previously,4 among clients who allowed the researchers to contact them, the response rate was 61.5%. Predominant reasons for nonparticipation were refusal due to health problems and cognitive impairment. Participants were aged 74.7 years (standard deviation ⫽ 8.3) on average, female (79.6%), white (73.9%), or black (19.7%), with 2.8% Hispanic ethnicity. Most had a high school education or more (33.8% high school; 27.5% less than high school; 38.7% more than high school), and were widowed (44.0%; 14.8% married; 33.1% divorced or separated; and 7.7% never married). Most reported their health as poor (35.9%) or fair (36.6%; 21.8% good; 4.2% very good; and 1.4% excellent). Most participants had two or more activities of daily living limitations (64.8%; 21.1% with 0; and 14.1% with 1), and all participants had at least two instrumental activities of daily living limitations, with 88.0% having four or more instrumental activities of daily living limitations (4.2% with two; and 7.7% with three). More details about participants’ characteristics are reported in the prior report.4
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Demographics. Participants reported age, sex, race, ethnicity, years of education, and marital status. Monthly Income. Monthly income was derived from the standard annual assessment by the case manager. Indicators of Physical Health. Participants selfrated their health using a five-point scale (1 ⫽ poor; 5 ⫽ excellent). The number of chronic physical health conditions was derived from the case manager’s report. The following chronic physical health conditions were provided: cancer, diabetes, emphysema, heart problems, liver problems, stroke, Parkinson disease, allergies, asthma, bladder/kidney problems, high blood pressure, gall bladder problems, and thyroid problems. Number of nonpsychotropic medications used was derived from either a list provided by the participant or a brown bag medication review with the participant. Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition-Axis I (Structured Clinical Interview for DSM-III-R [SCID22]). The SCID is a structured diagnostic interview that was used to diagnose Axis I disorders according to the Diagnostic and Statistical Manual of Psychiatric Disorders-IV.23 To minimize participant burden, questions were asked only in reference to current functioning, and only the following sections were included: major depressive episode, dysthymia, alcohol and substance abuse disorders, anxiety, and adjustment disorders. Independent ratings by the first author revealed substantial agreement between interviewers.4 Brief Symptom Inventory-18 (BSI-1824). For each of the 18 items, participants rate how much they have been bothered by the symptom for the past 7 days using a five-point scale (0 ⫽ not at all; 4 ⫽ extremely). It includes three subscales (depression, anxiety, and somatic; range: 0 –24) and a total score (range: 0 –72). Higher scores indicate more distress. This measure has been validated with various community and medical samples.24 In this sample, Cronbach alphas were 0.87 for depression, 0.81 for anxiety, 0.69 for somatic, and 0.89 for the total. Modified Mini-Mental State Examination (3MS25). The 3MS is a modification of the Mini-Mental State Examination,26 with four additional questions about similarities and revised scoring (range: 0 –100). It has
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Behavioral Health Service Utilization and Treatment superior validity and reliability compared with the Mini-Mental State Examination.25,27 Discrimination-Devaluation Scale (DDS28). The Discrimination-Devaluation Scale is the most widely used scale to assess mental health stigma and has good reliability and validity.28 It includes 12 items, rated using a six-point Likert scale (1 ⫽ strongly agree; 6 ⫽ strongly disagree). Six items are reverse scored. Items are summed and divided by 12 to result in a score range of 0 – 6. Higher scores represent greater stigma. Cronbach alpha in this sample was 0.70. Self-Identified Behavioral Health Problem. Participants were asked, “In the last 12 months, have you had a serious personal, emotional, or mental problem?” (yes/no29,30). Readiness to Change. Participants were asked about their readiness or attempts at making changes to reduce stress: “Have you attempted to reduce the amount of stress or sadness in your daily life?”31 Utilization of Behavioral Health Services. The interviewer recorded a list of participants’ current medications based on lists provided by participants or brown bag review. Medications were categorized into psychotropic classes (antidepressant, antianxiety, cognitive, and antipsychotic) according to lists of medications approved by the Federal Drug Administration and commonly used for each purpose, according to Julien32 and WebMD (accessed February 2008). The interviewer presented participants with a list (verbally and written) of professionals (psychologist/therapist/ counselor, social worker/case manager, psychiatrist, doctor [nonpsychiatrist], nurse, religious leader, alternative medicine professional, volunteer, and other) and asked “Have you ever seen any of these professionals to help deal with stress or sadness?”. Detailed questions followed for professionals seen within the past 12 months regarding type of treatment (prescribed medication, over-thecounter medication, case management, and talk therapy), location (primary care, emergency room, medical clinic, mental health clinic, senior center, religious setting, home, telephone), and frequency of visits (once/year, a few times/year, once/month, once/week, and nearly every day). These data were used to derive variables of professionals seen, types of treatment received, and location and frequency of visits for prescribed medication or counseling.
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Treatment Preferences, Facilitators, and Barriers. Participants were asked: “In the future, if you have problems with feelings of stress or sadness, which of these professionals would you be willing to go to for help?”. The same list of professionals, treatment types (support group added), and locations (residential setting added and emergency room omitted) from the questions on past service utilization were presented, and participants were asked which treatments and locations they would be willing to use. For each option participants were willing to use, they were asked to rank their most preferred. To identify barriers, participants were asked: “If you were having a problem with stress or sadness, would any of the following reasons stop you from getting any of these kinds of help, or from getting as much help as you may need?”. and were presented with a list of barriers. They were next asked, “Of these reasons, which would be the main reason you would not get help, or as much help as you may need?” This variable represented the “most influential barrier.” Similarly, they were asked about facilitators: “Would any of the following reasons make it more likely that you would get any of these kinds of help?” and were presented with a list of facilitators and asked to identify the “most influential facilitator.” Facilitators and barriers are listed in Table 4; these questions have been used in large-scale surveys of behavioral health service utilization.33 Procedures Interviews were conducted in participants’ homes. All measures were administered orally by research interviewers who were required to have at least a Bachelor’s degree in a relevant discipline and who were closely trained and supervised by the principal investigator (AG, licensed psychologist). Training and supervision involved use of official SCID training videotapes and materials, role play, and in-person and audiotaped review by the principal investigator. The only variable assessed by the case manager was monthly income, derived from the case manager’s routine assessment. Data Analysis SPSS Version 15.0 and STATA Version 9.2 were used for all statistical analyses. First, to examine
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Gum et al. services received, frequencies were derived for professional, location, and frequency of visits for psychotropic medication or counseling. To examine numbers of participants with Axis I disorders receiving services, frequencies were compared for those with and without an Axis I disorder. To examine covariates of service use, demographic (age, education, gender, monthly income, race/ethnicity, and marital status), clinical (self-rated health, SCID Axis I disorder, BSI-18, and 3MS), and helpseeking variables (stigma, self-identified behavioral health problem, and readiness to change) were compared for those who were taking psychotropic medications versus those not taking psychotropic medications. Bivariate comparisons were made using t tests for continuous variables and 2 for categorical variables. A similar comparison was not conducted for counseling because a small number of participants had received counseling in the past year (N ⫽ 21), and all but two of these individuals also received psychotropic medication. To further examine independent associations with psychotropic medication use, a multivariate logistic regression analysis was conducted with the following covariates: age (60 –93 years), gender (0 ⫽ male, 1 ⫽ female), race/ethnicity (0 ⫽ minority, 1 ⫽ white), years of education (0 –21), Axis I disorder (0 ⫽ no, 1 ⫽ yes), 3MS (64 –100), stigma (22–72), self-identified behavioral health problem (0 ⫽ no, 1 ⫽ yes), and readiness to change (0 ⫽ no, 1 ⫽ yes). These covariates were selected based on past research and the study hypotheses. Alpha of p ⱕ0.05 was used to determine significance in the final multivariate model. Frequencies were calculated for future willingness (yes/no) and most preferred for each professional, treatment modality, and location, as well as for all facilitators and barriers. Future willingness, facilitators, and barriers were compared for whites and minorities using 2 because of differences observed by race/ethnicity for service use.
RESULTS Current Use of Behavioral Health Services Table 1 displays details regarding the use of psychotropic medications and counseling. More than
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TABLE 1.
Characteristics of Psychotropic Medications and Counseling Received (N ⴝ 142) Axis I Disorder N (Row %) N (%)
Participants taking medications (n ⫽ 77, 54.2%) Category Any Antidepressant Antianxiety Cognitive Antipsychotic Antidepressant and antianxiety Number of categories 0 1 2 3 Prescribing professional (N ⫽ 51) Nonpsychiatrist MD Nurse Psychiatrist Location (N ⫽ 51) Primary care Other medical clinic Mental health clinic Emergency room Home Frequency of visits with prescribing professional (N ⫽ 50) One time/year Few times/year One time/month One time/week Nearly every day Participants receiving counseling (n ⫽ 21, 14.8%) Any Professional Psychologist/counselor Social worker Psychiatrist Location Primary care Other medical clinic Mental health clinic Emergency room Home Frequency One time/year Few times/year One time/month One time/week Nearly every day
No Yes (n ⴝ 107) (n ⴝ 31)
77 (100.0) 54 (70.1) 52 (67.5) 2 (2.6) 8 (10.4) 29 (37.7)
53 (71.6) 37 (69.8) 32 (65.3) 1 (100.0) 5 (62.5) 16 (57.1)
21 (28.4) 16 (30.2) 17 (34.7) 0 3 (37.5) 12 (42.9)
65 (45.8) 44 (57.1) 27 (35.1) 6 (7.8)
54 (84.4) 34 (81.0) 16 (59.3) 3 (60.0)
10 (15.6) 8 (19.0) 11 (40.7) 2 (40.0)
41 (80.4) 2 (3.9) 16 (31.4)
23 (59.0) 1 (50.0) 9 (56.3)
16 (41.0) 1 (50.0) 7 (43.8)
30 (58.8) 9 (17.6) 15 (29.4) 1 (2.0) 4 (7.8)
16 (57.1) 12 (42.9) 6 (66.7) 3 (33.3) 7 (50.0) 7 (50.0) 1 (100.0) 0 3 (75.0) 1 (25.0)
6 (12.0) 27 (54.0) 12 (24.0) 3 (6.0) 2 (4.0)
2 (33.3) 4 (66.7 16 (59.3) 11 (40.7) 6 (60.0) 4 (40.0) 3 (100.0) 0 2 (100.0) 0
21 (100.0) 12 (57.1) 14 (66.7) 8 (57.1) 2 (9.5) 0 10 (47.6) 5 (50.0)
9 (42.9) 6 (42.9) 2 (100.0) 5 (50.0)
0 3 (14.3) 13 (61.9) 1 (4.8) 6 (28.6)
0 3 (100.0) 6 (46.2) 1 (100.0) 3 (50.0)
0 0 7 (53.8) 0 3 (50.0)
5 (23.8) 7 (33.3) 7 (33.3) 1 (4.8) 1 (4.8)
5 (100.0) 4 (57.1) 3 (42.9) 0 0
0 3 (42.9) 4 (57.1) 1 (100.0) 1 (100.0)
Notes: Of the total sample (N ⫽ 142), 77 (54.2%) were prescribed psychotropic medications per the interviewer’s medication review and 21 (14.8%) reported receipt of counseling. For medications, prescribing professional (N ⫽ 51), location where prescribing professional was seen (N ⫽ 51), and frequency of visits with prescribing professional (N ⫽ 50) have missing data because some of the 77 participants did not self-identify as taking psychotropic medications and therefore did not report this information. Some numbers may add up to more than the totals due to a small number of participants seeing multiple professionals. Four participants were missing data for Axis I disorder; therefore the rows may not add up to the overall total in some cases.
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Behavioral Health Service Utilization and Treatment half of the sample was using at least one prescribed psychotropic medication (N ⫽ 77; 54.2%). Of the 77 participants who had psychotropic medications recorded by the interviewer, only 51 reported taking a psychotropic medication. Therefore, prescribing professional, location, and frequency of visits are missing for 26 individuals. Among those 51 reporting taking psychotropic medications, most received their prescriptions from a nonpsychiatrist medical doctor (N ⫽ 41, 80.4%) in a primary care setting (N ⫽ 30, 58.8%), for a few visits a year (N ⫽ 27, 54.0%). The highest percentage were taking antidepressants (N ⫽ 54, 70.1%) or antianxiety medications (N ⫽ 52, 67.5%), with a third taking two or more categories of psychotropic medication (N ⫽ 33, 42.9%). Of those taking an antidepressant or antianxiety medication, approximately one-third continued to meet criteria for an Axis I disorder (N ⫽ 16, 30.2% and N ⫽ 17, 34.7%, respectively). Also shown in Table 1, 21 participants (14.8%) reported having received counseling within the past year. Counseling was delivered primarily by a psychologist or counselor (N ⫽ 14, 66.7%) or psychiatrist (N ⫽ 10, 47.6%) in a specialty mental health clinic (N ⫽ 13, 61.9%). The frequency of counseling received was extremely low, however, at only a few times a year or less for the majority (N ⫽ 12, 57.1%). Table 2 presents comparisons of demographic and clinical variables according to psychotropic medication use. Those taking psychotropic medications were younger and more likely to be white; be taking more nonpsychotropic medications, have more chronic health conditions, be diagnosed with an anxiety disorder; have greater somatic, anxiety, and overall symptoms on the BSI-18; self-identify having a behavioral health problem; and report attempting to change. Of those diagnosed with an Axis I disorder, two-thirds (N ⫽ 21, 67.7%) were taking a psychotropic medication. In the multivariate logistic regression (N ⫽ 136; four missing Axis I disorder, one missing stigma scale, and one missing self-identified problem), only age and race were independently associated with being prescribed psychotropic medication. Participants were more likely to use psychotropic medications if they were younger (odds ratio ⫽ 0.929, 95% confidence interval ⫽ 0.883– 0.977, z [1] ⫽ 8.227, p ⫽ 0.004) and white (odds ratio ⫽ 4.341, 95% confidence
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interval ⫽ 1.644 –11.464, z [1] ⫽ 8.782, p ⫽ 0.003). No other covariates were significant (all p ⬎ 0.05).
Treatment Preferences, Facilitators, and Barriers As shown in Table 3, participants were willing to utilize a variety of professionals, treatment modalities, and locations. Almost all were willing to see at least one professional (N ⫽ 138, 97.2%) and try prescribed medications or counseling (N ⫽ 128, 90.1%). The largest numbers of participants were willing to see their primary care physician (N ⫽ 103, 72.5%), psychologist/counselor (N ⫽ 96, 67.6%), or case manager (N ⫽ 87, 61.3%), with primary care physician (N ⫽ 36, 25.4%) as the most preferred professional. Nearly equal numbers were willing to try prescribed medication (N ⫽ 105, 73.9%), counseling (N ⫽ 102, 71.8%) or case management (N ⫽ 104, 73.2%), with prescribed medication (N ⫽ 49, 34.5%) or counseling (N ⫽ 36, 25.4%) as the most preferred treatment type. Most participants were willing to receive services in their homes (N ⫽ 109, 76.8%), doctor’s office (N ⫽ 103, 72.5%) or a mental health office (N ⫽ 89, 62.7%), with home (N ⫽ 42, 29.6%) or doctor’s office (N ⫽ 33, 23.2%) as the most preferred locations. Facilitators and barriers are presented in Table 4. The most common facilitators that increased participants’ likelihood of seeking help were symptoms too severe to handle (N ⫽ 114, 80.3%), encouragement from others (N ⫽ 102, 71.8%), and financial assistance (N ⫽ 102, 71.8%), with symptoms too severe to handle reported as the most influential facilitator by the largest number of participants (N ⫽ 49, 34.5%). The most common barriers were affordability (N ⫽ 102, 71.8%), difficulty traveling (N ⫽ 89, 62.7%), and lack of transportation (N ⫽ 65, 45.8%). Affordability was the single most influential barrier (N ⫽ 46, 32.4%). Given the differences in psychotropic medication use by race, we examined future willingness, facilitators, and barriers by race (white, minority) using Pearson 2 analyses and Fisher’s exact tests. None of the willingness or barrier variables were significant (all p ⬎0.05). Only one facilitator differed significantly, getting help with transportation, 2[1] 6.90, p ⫽ 0.009, which was identified by 80.6% of minorities and 55.9% of whites.
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Gum et al.
TABLE 2.
Psychotropic Medication Use by Demographic and Clinical Characteristics (N ⴝ 142)
Age in years, M (SD) Education in years, M (SD) Gender Male Female Monthly income in dollars, M (SD) Race White Black Hispanic Native American Asian Multiracial Marital status Married Separated/divorced Never married Widow/widower Self-rated health Poor Fair Good Very good/excellent Nonpsychotropic medications M (SD) Chronic medical conditions M (SD) Any SCID disorder Any depressive MDE Substance Anxiety Adjustment disorder-depression Adjustment disorder-anxiety Adjustment disorder-mixed BSI-18 somatic, M (SD) BSI-18 depression, M (SD) BSI-18 anxiety, M (SD) BSI-18 total, M (SD) 3MS, M (SD) Stigma scale, M (SD) Self-identified problem (yes) Attempted change (yes)
No Medication (n ⴝ 65), N (%) or M (SD)
Medication (n ⴝ 77), N (%) or M (SD)
t (df) or 2 (df)
p
77.58 (8.36) 12.03 (3.20)
72.31 (7.52) 12.51 (2.28)
3.96 (140) ⫺1.03 (140)
⬍0.01 0.30
13 (44.8) 52 (46.0) 1005.05 (543.41)
16 (55.2) 61 (54.0) 976.68 (493.92)
0.01 (1)
0.91
0.33 (140)
0.75 ⬍0.01
40 (38.1) 20 (71.4) 2 (50.0) 1 (100.0) 0 2 (66.7)
65 (61.9) 8 (28.6) 2 (50.0) 0 1 (100.0) 1 (33.3)
—
9 (42.9) 22 (46.8) 1 (9.1) 33 (52.4)
12 (57.1) 25 (53.2) 10 (90.9) 30 (47.6)
7.16 (3)
0.07
—
0.45
19 (37.3) 24 (46.2) 18 (58.1) 4 (50.0) 6.63 (4.28) 4.25 (2.11) 10 (32.3) 5 (29.4) 5 (31.3) 2 (66.7) 4 (23.5) 2 (40.0) 2 (40.0) 5 (71.4) 4.60 (3.93) 3.25 (4.30) 2.63 (3.23) 10.48 (8.84) 87.62 (8.61) 44.81 (9.47) 14 (31.8) 38 (39.2)
32 (62.7) 28 (53.8) 13 (41.9) 4 (50.0) 8.30 (4.54) 5.73 (2.82) 21 (67.7) 12 (70.6) 11 (68.8) 1 (33.3) 13 (76.5) 3 (60.0) 3 (60.0) 2 (28.6) 6.41 (4.83) 4.91 (5.84) 4.62 (5.19) 15.93 (13.88) 88.57 (8.53) 46.87 (9.16) 30 (68.2) 59 (60.8)
⫺2.24 (140) ⫺3.49 (140) 3.21 (1) 2.08 (1) 1.53 (1) — 4.07 (1) — — — ⫺2.41 (140) ⫺1.90 (140) ⫺2.69 (140) ⫺2.74 (140) ⫺0.66 (140) ⫺1.31 (139) 5.25 (1) 5.37 (1)
0.03 0.01 0.07 0.15 0.22 0.59 0.05 1.00 1.00 0.25 0.02 0.06 ⬍0.01 ⬍0.01 0.51 0.19 0.02 0.02
Notes: Four missing Axis I disorder, one missing stigma scale, and one missing self-identified problem. Pearson 2 statistics are reported, except for race, self-reported health, substance abuse disorder, and the adjustment disorder variables. For these variables, Fisher’s exact test statistics are reported due to some cells with expected values ⬍5. SD: standard deviation.
DISCUSSION Broadly, the study findings indicate that aging network clients receiving home-based services have ready access to psychotropic medications but receive very few specialty behavioral health services and medication monitoring visits. They are willing to use a variety of behavioral health services and perceive mainly practical barriers to using services. The use of
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prescribed medications was quite high (54.2%); ⬎70% of participants diagnosed with an Axis I depressive or anxiety disorder in the research interview were taking at least one psychotropic medication. This result suggests that providers recognized and were attempting to address clients’ behavioral health issues, although the finding that many clients taking medications (⬎30%) continued to meet diagnostic criteria suggests that usual care is insufficient. The quality and intensity of medication management re-
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Behavioral Health Service Utilization and Treatment
TABLE 3.
Future Treatment Preferences for Behavioral Health Services
Any professional Professional type Psychologist/counselor Social worker/case manager Psychiatrist Primary care physician Nurse Religious/spiritual leader Alternative medicine healer Volunteer Other Relative/friend Home health aide Alcoholics Anonymous Lay minister Treatment modality Prescribed medication Over-the-counter medication Psychotherapy/counseling Support group Case management Location Mental health office/clinic Doctor’s office Senior center Residential facility Religious/spiritual setting Home Telephone
Willing, N (%)
Most Preferred, N (%)
138 (97.2)
—
96 (67.6) 87 (61.3) 74 (52.1) 103 (72.5) 71 (50.0) 76 (53.5) 31 (21.8) 52 (36.6) 37 (26.1) 28 (19.7) 7 (4.9) 1 (0.7) 1 (0.7)
19 (13.4) 9 (6.3) 17 (12) 36 (25.4) 5 (3.5) 24 (16.9) 2 (1.4) 3 (2.1) 23 (16.2) — — — —
105 (73.9) 44 (31.0) 102 (71.8) 78 (54.9) 104 (73.2)
49 (34.5) 3 (2.1) 36 (25.4) 19 (13.4) 26 (18.3)
89 (62.7) 103 (72.5) 54 (38.0) 43 (30.3) 67 (47.2) 109 (76.8) 71 (50.0)
19 (13.4) 33 (23.2) 5 (3.5) 4 (2.8) 16 (11.3) 42 (29.6) 16 (11.3)
Notes: One missing for all variables; numbers for most preferred do not always add to 138 due to a small number of participants who refused to rank options they were willing to use. All percentages are based on the total sample, N ⫽ 142.
ceived may have contributed to clients’ persistence of symptoms. Almost all medications were received from nonpsychiatrists in nonspecialty settings, where quality of behavioral health services tends to be lower than in specialty settings.8 Although depressed older adults require ongoing medication monitoring and switching to achieve remission,34 most participants (66%) only saw the prescribing professional a few times per year. Use and intensity of counseling were also low. Although a sizable minority (14.8%) reported receipt of counseling within the past year, frequency of visits was extremely low (once a month or less for 90.5% of those receiving counseling). Almost all those receiving counseling were also taking medications. Participants may have labeled medication visits or occasional discussions with providers regarding their
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TABLE 4.
Facilitators and Barriers to Accessing Behavioral Health Services
Facilitators If my symptoms became too severe to handle If others encouraged me to seek help Getting help to pay for it Getting help with transportation Finding out where to go to get help Barriers I couldn’t afford the money It’s hard to travel to appointments I don’t have transportation I prefer to manage it myself I don’t want to take more medication I think it’s better to keep these matters private I think it would go away by itself I don’t know where to go to get help I would get help from another source My symptoms would interfere with seeking help I don’t think treatment would help The problem wouldn’t bother me I am concerned to ask or what others would think I don’t have time
Facilitator/ Barrier Identified (yes), N (%)
Most Influential Facilitator/ Barrier, N (%)
114 (80.3)
49 (34.5)
102 (71.8)
9 (6.3)
102 (71.8) 86 (60.6)
26 (18.3) 32 (22.5)
73 (51.4)
12 (8.5)
102 (71.8) 89 (62.7)
46 (32.4) 9 (6.3)
65 (45.8) 62 (43.7) 54 (38.0)
31 (21.8) 12 (8.5) 8 (5.6)
46 (32.4)
9 (6.3)
42 (29.6)
2 (1.4)
39 (27.5)
5 (3.5)
39 (27.5)
4 (2.8)
28 (19.7)
1 (0.7)
21 (14.8)
3 (2.1)
21 (14.8)
0
20 (14.1)
2 (1.4)
8 (5.6)
0
Notes: One to six responses missing across items. All percentages are based on the total sample, N ⫽ 142.
moods as “counseling” sessions. Thus, although clients may occasionally access providers for some type of discussion, receipt of counseling at a frequency comparable to evidence-based psychotherapy35 is extremely rare. Consistent with hypotheses, participants were open to a range of behavioral health services. More than 90% were willing to try either medication or counseling; indeed, more than half of participants were already taking some form of psychotropic medication. These findings are also consistent with other recent research9 and counters the assumption that
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Gum et al. older adults are not open to using behavioral health services. Relevant to the aging network, most clients were willing to discuss behavioral health issues with a case manager (61%) and receive case management for distress (73%). Home and primary care physicians’ offices were the locations in which most participants were open to receiving services. As expected, the most commonly reported barriers were practical: finances, difficulty traveling to appointments, and lack of transportation. Alternatively, the most common and influential facilitator was related to perceived need: if symptoms became “too severe to handle.” Unfortunately, it is not possible to determine each client’s definition of symptoms that are “too severe.” Our prior research with this sample suggest that older adults’ perceptions of their behavioral health problems are complex and not necessarily related to severity of symptoms; rather, perceptions were associated with their familiarity of behavioral health issues in other people.4 Enhancing affordability, access to transportation, and being encouraged by others to seek help were also common facilitators. Taken together, these findings suggest that most of the older adults are open to discussing distress they are experiencing and behavioral health services. Specifically, professionals may be able to facilitate service use by educating the older person about behavioral health problems, helping the person become familiar with symptoms and when treatment is indicated, and reducing practical barriers. Consistent communication between professionals and older adults pertaining to these areas may help reduce stigma and increase commitment to engage in behavioral health treatments. Findings suggest that case managers in the aging network can overcome a number of identified barriers to increase access to behavioral health services. They are well positioned to conduct in-home screening and symptom monitoring, similar to an effective screening and referral intervention implemented in home healthcare.21 Case managers can also provide psychoeducation that incorporates facilitators to service use such as information about symptom severity and encouraging service use. Moreover, case managers can increase access to counseling by integrating counseling with case management, a promising approach based on one study with low-income older adults36 and research with younger age groups.37 The findings also suggest that case managers need to work closely with primary care providers, given
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the high use of and preference for medications from primary care. Comprehensive case management in collaboration with primary care providers may facilitate clients’ ability to access primary care services, although case managers have reported challenges collaborating with primary care.38 This collaboration may also reduce the racial and ethnic disparity that was observed for medication use, given that research in primary care has demonstrated that depression care management can remove disparities in access for minority elders.39 Several limitations should be considered. The most important limitation concerns the generalizability of the sample, given the relatively small sample size and restricted geographical area. One particular threat to generalizability is the selection bias, as participants represent a convenience sample recruited by case managers. As reported previously,4 compared with the full caseload of clients in the same region of Florida, participants were slightly younger on average, less likely to be Hispanic, and slightly less limited in activities of daily livings. Thus, the findings likely do not generalize to the most frail clients and Hispanic clients. Receipt of psychotropic medications with appropriate monitoring and counseling are likely to be even lower for these groups of older adults than for the current sample, given the additional barriers to service use faced by especially frail elders with limited mobility and Hispanic clients who may not speak fluent English. Cognitive impairment is likely an additional complicating factor in service delivery for the frailest clients. If these hypotheses are correct, then case managers could play a particularly essential role in service delivery to these older adults, if they can communicate in Spanish and deliver services in clients’ homes. A second limitation is the lack of assessment of bipolar disorder; this section of the SCID was omitted to minimize participant burden, but the possibility of some participants identified with major depressive episodes actually having bipolar disorder cannot be ruled out. Third, details are not available regarding the quality of services provided, such as medication dosage or length of time on medications. Unfortunately, some of the participants who were identified as being prescribed psychotropic medications per medication review did not self-identify as taking such medications, resulting in missing data for additional details regarding the prescribing pro-
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Behavioral Health Service Utilization and Treatment fessional. Despite these limitations, we believe that the findings provide an important basis for beginning to implement behavioral health interventions in the aging network. Moreover, the validity of the findings is corroborated by other studies with older adults, which have also found low use of specialty services,8,9 high use of general medical services,40 high willingness to use services,9 and predominantly practical barriers to accessibility.3 Future research is needed to adapt behavioral interventions for the aging network to match clients’ needs and preferences and characteristics of the aging network. One promising avenue is the development of strategies to facilitate case managers’ collaboration with primary care to comprehensively manage clients’ depression and anxiety through screening, referral, and interventions delivered in home and primary care. Other potential areas of
inquiry include training case managers to conduct screening, make referrals, and encourage clients’ engagement in services. By utilizing the vast resources of the aging network, such as clients’ existing relationships with case managers who make home visits, the aging network has exceptional potential to reach vulnerable older adults, thereby enhancing access to services and behavioral health outcomes.
The authors thank the older adults who participated in this study and the aging service agencies that collaborated with us to complete this study: Community Aging and Retirement Services, Inc., Gulf Coast Jewish Family Services, Hillsborough County Aging Services, and Polk County Elderly Services. This work was supported by a grant from University of South Florida New Researcher (to AMG).
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