600 Suicide and Life-Threatening Behavior 45 (5) October 2015 © Published 2015. This article is a U.S. Government work and is in the public domain in the USA DOI: 10.1111/sltb.12154
Telehealth Monitoring of Patients with Schizophrenia and Suicidal Ideation JOHN KASCKOW, MD, PHD, SHASHA GAO, PHD, BARBARA HANUSA, PHD, ARMANDO ROTONDI, PHD, MATTHEW CHINMAN, PHD, SUSAN ZICKMUND, PHD, JOHN GURKLIS, MD, LAUREN FOX, BS, JACK CORNELIUS, MD, IRA RICHMOND, DNP, RN, AND GRETCHEN L. HAAS, PHD
A telehealth system was developed to monitor risk following hospitalization for suicidal ideation. We hypothesized that 3 months of telehealth monitoring will result in a greater reduction in suicidal ideation. Veterans with schizophrenia admitted with recent suicidal ideation and/or a suicidal attempt were recruited into a discharge program of VA Usual Care with daily Health Buddy© monitoring (HB) or Usual Care (UC) alone. Fifteen of 25 were randomized to HB and 10 received UC. Daily adherence in the use of the HB system during months 1–3 was, respectively, 86.9%, 86.3%, and 84.1%. There were significant improvements in Beck Scale for Suicide Ideation scores in HB participants. There were no changes in depressive symptoms. Telehealth monitoring for this population of patients appears to be feasible.
Suicide is a leading cause of premature death among people with schizophrenia (Pompili et al., 2007). Suicide is also a major public health problem among veterans. Suicide rates for male and female veterans are approximately two times higher than in the general population (Blow et al., 2012; McCarthy et al., 2009). Suicide is also a leading cause of
premature death among veterans with schizophrenia. Ilgen et al. (2010) reported that veterans with schizophrenia have suicide rates of 83.3 per 100,000. Risk factors for suicide include the presence of previous attempts, an early age of onset of illness, and coexisting depressive symptoms. Patients with schizophrenia are
JOHN KASCKOW, VA Pittsburgh MIRECC, CHERP and Behavioral Health, Pittsburgh, PA, USA, and UPMC Western Psychiatric Institute and Clinic, Pittsburgh, PA, USA; SHASHA GAO, VA Pittsburgh CHERP, Pittsburgh, PA, USA; BARBARA HANUSA, VA Pittsburgh MIRECC, Pittsburgh, PA, USA; ARMANDO ROTONDI, VA Pittsburgh MIRECC, Pittsburgh, PA, USA, and UPMC Critical Care, Pittsburgh, PA, USA; MATTHEW CHINMAN, VA Pittsburgh MIRECC and CHERP, Pittsburgh, PA, USA; SUSAN ZICKMUND, VA Pittsburgh CHERP, Pittsburgh, PA, USA, and UPMC Department of Medicine, Pittsburgh, PA, USA; JOHN GURKLIS, VA Pittsburgh Behavioral Health, Pittsburgh, PA, USA; LAUREN FOX, VA Pittsburgh MIRECC, Pittsburgh, PA, USA; JACK CORNELIUS, VA Pitts-
burgh MIRECC, Pittsburgh, PA, USA, and UPMC Western Psychiatric Institute and Clinic, Pittsburgh, PA, USA; IRA RICHMOND , VA Pittsburgh Patient Care Services, Pittsburgh, PA, USA; GRETCHEN L. HAAS, VA Pittsburgh MIRECC and Behavioral Health, Pittsburgh, PA, USA, and UPMC Western Psychiatric Institute and Clinic, Pittsburgh, PA, USA. Funded by the VISN 4 MIRECC and HSRD PPO 10-249-2 (JWK). The views do not represent the views of the U.S. Department of veterans Affairs or that of the U.S. government. Address correspondence to John Kasckow, VA Pittsburgh Health Care System, University Drive C, Behavioral Health (116a), Pittsburgh, PA 15240; E-mail: [email protected]
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also more likely to commit suicide within the first few weeks or months after a hospital discharge (Cannon, Buckley, & Larkin, 1991; Desai, Dausey, & Rosenheck, 2005). Among hospitalized patients, postdischarge suicide rates are as high as 310 per 100,000 for patients with schizophrenia, with 46% of suicides occurring within the first 3 months postdischarge (Desai et al., 2005). The relationship between hospital discharge and suicide may be related to these patients experiencing a “postpsychotic depression” (Siris, 2001; Pompili, Mancinelli, & Tatarelli, 2003). It is believed that people with schizophrenia whose symptoms improve while in the hospital subsequently gain insight into their life circumstance which then appears to increase the risk for suicide after hospital discharge. Telepsychiatric interventions, which include telephone, Internet or video, show promise in providing easy-to-access services (Jennett et al., 2003). Telepsychiatry can be used as a useful way to monitor factors in individuals at risk for suicidal behavior. Worsening depressive symptoms, psychosis, and substance abuse (Hawton, Sutton, Haw, Sinclair, & Deeks, 2005) as well as the impact of early life and recent events (Pompili et al., 2011) have been cited as important risk factors. Risk factors could be monitored and addressed as indicated with telehealth systems to reduce suicide risk. Initial progress with the use of telephone-, video-, and Internet-based modalities has been made in the treatment of patients with schizophrenia (Bensink, Hailey, & Wooton, 2006; Kasckow, Felmet, et al., 2014; Rotondi, Eack, Hanusa, Spring, & Haas, 2013). The initial studies have demonstrated that the use of telehealth is feasible and in some cases has been shown to improve outcomes. One pilot study by Beebe (2001) examined the effectiveness of a telephone intervention (TIPS) for patients with schizophrenia; this intervention focused on problem solving, coping alternatives, and providing reminders to clients to use alternative coping strategies. The experimental TIPS group included 3 months of weekly telephone calls along with routine commu-
601 nity care. Compared to treatment as usual, there was a suggestion that patients in the experimental group spent more time in the community with fewer numbers of hospitalizations; however, this difference was not statistically significant. A later study by this group and others indicated that telenursing paradigms in patients with schizophrenia have been shown to enhance patient clinician communication and medication adherence (Beebe et al., 2008; Frangou, Sachpazidis, Stassinakis, & Sakas, 2005). We have developed a telehealth system for suicidal patients with schizophrenia using the Health Buddy© (Bosch Health Care, Tampa, FL, USA) system, a device that facilitates symptom assessment and patient–staff communication between outpatient visits. It is a device that is user friendly and is ideal for patients with possible cognitive impairment, including those with schizophrenia. This study involved a comparison of VA Usual Care to VA Usual Care augmented by daily use of the Health Buddy© system in a random-assignment clinical trial. We monitored both suicidal ideation and depressive symptoms as both are major risk factors for suicide in patients with schizophrenia (Hawton et al., 2005). In the trial, we tested the hypothesis that use of the telehealth system would result in a greater reduction in both suicidal ideation and depressive symptoms on standardized measures following discharge from an inpatient service, relative to a group that received only VA Usual Care. In addition, feasibility of telehealth monitoring for suicidal behavior in this population was assessed by tracking the use of the telehealth system by participants.
METHODS
Design This was a randomized clinical trial. Eligible participants were randomized to one of the two study arms: VA Usual Care (UC; control) or UC with daily Health
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Buddy© monitoring (HB; Treatment). Recruitment occurred from February 2012 to May 2013. All participants received assessments with the Beck Scale for Suicidal Ideation scores (SSI; Beck, Kovacs, & Weissman, 1979) and the Calgary Depression Rating Scale on baseline (before the Health Buddy© was installed), and at weeks 2, 4, 8, and 12 after the Health Buddy© was installed in the HB group. Sample We obtained a prescreening waiver from our internal review board (IRB) to examine medical records of veterans age 18 and older who were recently admitted. Patients’ admission records were examined to determine whether patients exhibited recent suicidal ideation or a recent suicide attempt and also whether they had a diagnosis of schizophrenia or schizoaffective disorder; if an eligible patient was found, the clinician would be asked to refer the patient. If the patient was interested, consent was obtained. Patients were further screened for the following inclusions: a Mini Mental Status score ≥21 to rule out individuals with marked cognitive impairment (Folstein, Folstein, & McHugh, 1975); lack of a medical disorder that could influence diagnostic decisions, safety, and/ or anticipated adherence so that individuals could follow through with the protocol daily; and a score >0 on items 4 or 5 on the SSI, which indicated whether the patient had active and/or passive suicidal ideation in the past week. In addition, we administered the Mini-International Neuropsychiatric Interview 6.0 (MINI) to determine whether patients had a diagnosis of schizophrenia or schizoaffective disorder (Sheehan et al., 1998). We also obtained demographic data (see Table 1). Procedures All procedures were approved by the IRB of the VA Pittsburgh Health Care System. All eligible consenting participants
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were screened initially by a nonresearch social worker to assess capacity for consent. This consisted of six questions testing knowledge about what the study involved. If participants scored 80% or higher, they were then considered for informed consent. The IRB at our institution decided that a score of 80% or higher was required. Usual Care With UC, all participants saw their clinician within 2 weeks after discharge and had their medications periodically managed by their psychiatrist or nurse practitioner. Some participants received more intensive treatment. Intensive treatment included the VA Psychosocial Residential Rehabilitation Treatment Program (PRRTP) which provides a structured and supportive residential environment (24 hr/7 days a week) as a part of the rehabilitative treatment regime for veterans with substance use disorders. In addition, participants may have stayed in a personal care home. Health Buddy© Participants in this group received UC in addition to HB monitoring. Each participant in the telehealth condition had either a wireless modem device or a Health Buddy© device connected to their landline telephone. Each day, for 10 to 15 minutes, the Health Buddy© administered a series of text-based questions that were displayed on the Health Buddy© screen called “dialogues.” The dialogues focused on monitoring symptoms of depression, psychosis, suicide, substance use, and medication adherence. Each button corresponded to a different response (e.g., “yes” vs. “no” or “this has been a problem,” “a little bit,” “sometime,” “much of the time”), and responses for each button varied with each question. Immediately after the participant responded to the dialogues, participant responses were electronically transferred to a secure website and read by nursing staff within 4 hours.
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603
TABLE 1
Baseline Characteristics by Treatment Measure Age (years) M SD Race Black White Education (in years) M SD Marital Status Married/Living with a partner Separated/Divorced/Widowed Never married Received additional treatment after discharge? (Yes) Alcohol dependence in past 12 months Substance dependence in past 12 months Schizophrenia Schizoaffective disorder Prior suicide attempts? (none vs. 1 or more)
Total (N = 25)
HB (n = 15)
UC (n = 10)
52.5 12.9
55.8 10.8
47.5 14.7
17 (68.0%) 8 (32.0%) 12.8 1.9 6 11 8 5
(24.0%) (44.0%) (32.0%) (20.0%)
9 (60.0%) 6 (40.0%)
8 (80.0%) 2 (20.0%)
p value .12
.40
12.9 2.2
12.8 1.4
.94
5 7 3 3
1 4 5 2
.22
(33.3%) (46.7%) (20.0%) (20.0%)
(10.0%) (40.0%) (50.0%) (20.0%)
>.99
6 (24.0%)
1 (6.7%)
5 (50.0%)
.02
6 (24.0%)
2 (13.3%)
4 (40.0%)
.18
13 (52.0%) 12 (48.0%) 18 (72.0%)
6 (40.0%) 9 (60.0%) 10 (66.7%)
7 (70.0%) 3 (30.0%) 8 (80.0%)
.23 .23 .66
Note: Independent samples t test was performed for continuous variables; Fisher exact test was used for categorical variables. For continuous variables, M = mean and SD = standard deviation; for categorical measures, data are expressed as N (percentages).
The HB dialogues provided daily supportive psychoeducational material. For instance, the dialogues would help participants decide when to contact their clinician when various symptoms got worse, such as psychotic symptoms (e.g., worsening guilty ideas of reference or hallucinations) or depressive symptoms (e.g., worsening sleep disturbance, depressed mood, or hopelessness). The dialogues would also provide participants contact numbers for the crisis line if they developed worsening suicidal intent and/or plan. The dialogues would monitor symptoms of substance use; for instance, if participants responded “yes” to a question inquiring as to whether they had three or more drinks within 24 hours, the dialogue would comment that this is concerning and that they should seek our help for this. The
dialogues would also encourage participants to engage in recovery focused behavior such as reaching out to friends or family members in time of need. Copies of the dialogues utilized are available upon request. The dialogues used were modified from the original ones which had been provided by Bosch Health Care (the company which markets the Health Buddy©) using patient-centered design methods as described by Nielsen (1994). As described in Kasckow, Zickmund, et al. (2014), we initially convened a panel of consumers and academic experts in suicidology, substance abuse and schizophrenia, recovery, information technology for seriously mentally ill individuals, and early warning signs of schizophrenia. Initial modifications were made based on their recommendations.
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We then recruited participants with schizophrenia or schizoaffective disorder and a history of suicidal ideation and/or suicidal attempt. With a research assistant, participants read through the dialogue scripts and commented as to whether they understood the intended meaning. Participants were also encouraged to suggest changes. The sessions were recorded and when all participants completed the testing, the recordings were subjected to a qualitative analysis. Coders derived prominent themes; these themes were discussed with the research team and final changes were made to the dialogues as described by Kasckow et al. (2014). Measures Sociodemographic information collected at baseline included age, race, education, and marital status. Dependent variables included the SSI (Beck et al., 1979) and the Calgary Depression Rating Scale scores (CDRS; Addington, Addington, & Atkinson, 1996). Assessors were not masked to intervention arm. The SSI has been used to assess suicidal ideation in various populations including those with schizophrenia and schizoaffective disorder as well as veterans (Pinninti, Steer, Rissmiller, Nelson, & Beck, 2002; Bell & Nye, 2007; Zisook et al., 2010). The SSI scale contains 21 items which are rated on a scale of 0 to 2. The maximal score is 38. Higher scores are indicative of higher levels of suicidal ideation. If an individual scores “0” on items 4 or 5, which respectively assesses active or passive suicidal ideation, then only questions 1–5, 20, and 21 are completed; questions 20 and 21, respectively, ask whether the participant had ever attempted suicide and if so, how serious the attempt was. If an individual scores >“0” on items 4 or 5 (or both), then the remaining 6–19 questions are completed. Scores from items 1– 19 are then included in the final score. Examples of the scale items from the SSI include the following. For Item 4: (0) I have no desire to kill myself, (1) I have a weak
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desire to kill myself, (2) I have a moderate to strong desire to kill myself; for Item 5: (1) I would try to save my life if I found myself in a life-threatening situation, (2) I would take a chance on life or death if I found myself in a life-threatening situation, (3) I would not take the steps necessary to avoid death if I found myself in a life-threatening situation. The CDRS has been shown to specifically assess depression in patients with schizophrenia; this scale has also been used in veteran populations (Addington, Addington, Maticka-Tyndale, & Joyce, 1992; Addington et al., 1996; Kasckow, Golshan, & Zisook 2014). The CDRS is a nine item scale; each question has a 4-point response from 0 to 3 with a maximal total score of 27. As an example, Item 7 states the following: Early Awakening: Do you wake earlier in the morning than is normal for you? How many times a week does this happen? (0) No early awakening, (1) Mild: occassionally wakes (up to twice weekly) 1 hr or more before normal time to wake or alarm time, (2) Moderate: often wakes early (up to five times weekly) 1 hr or more before normal time to wake or alarm time, (3) Severe: Often wakes 1 hr or more before normal time. As another example, item 6 states Morning Depression: When you have felt depressed over the last 2 weeks have you noticed the depression being worse at any particular time of day? (0) Absent: No depression, (1) Mild: Depression present but no diurnal variation, (2) Moderate: Depression spontaneously mentioned to be worse in a.m., (3) Severe: Depression markedly worse in a.m., with impaired functioning which improves in p.m. Analysis We calculated descriptive statistics on all study variables. Continuous measures were expressed as means and standard deviations; categorical measures were expressed by frequency and percentage. We conducted two group t test or Fisher exact tests to compare UC and HB groups on continuous and categorical sociodemographic variables, as appropriate. Outcome variables
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were compared between UC and HB groups at each time point (baseline, 2, 4, 8, and 12 weeks) using the Kruskal–Wallis test for continuous outcomes or chi-square tests for categorical outcomes. To assess feasibility, we monitored levels of daily adherence to telehealth monitoring. Adherence was defined as the percentage of days active participants downloaded responses to the questions on the HB. To test our hypotheses, we compared changes in the HB and UC groups’ SSI scores and CDRS scores at baseline, 2, 4, 8, and 12 weeks. The primary independent variable was the randomized treatment arm (HB or UC). Mixed effect regression modeling was used to examine the relationship between treatment assignment and primary outcomes. Fixed effects included time and treatment group, and their interaction. The variables that were significantly different at baseline between HB and UC groups were controlled in the model as well. The primary treatment effect examined in these models was the treatment by time interaction. The statistical significance of main effects and interactions was assessed using Wald statistics. We used orthogonal polynomials, computed via the Cholesky decomposition to avoid high correlation between original “time” scale variables, which can cause estimation problems (Narayan & Hesthaven, 2012). SAS 9.3 (SAS Institute Inc., Cary, NC, USA) was used for the analysis.
RESULTS
A total of N = 1,147 unique veterans were screened between February 2012 and May 2013 from the inpatient unit of the VA Pittsburgh Health Care System. Figure 1 depicts details of the recruiting process to the point of randomization. Of those randomized, 15 were randomized to the HB group and 10 were randomized to UC. Fourteen of 15 participants could set up the system and report their symptoms through the system. Thirteen (86.7%) of the HB and 7 (70.0%) of the UC group
605 completed at least one follow-up interview. Overall, 11 (73.3%) of the HB group and 6 (60.0%) of the UC group completed all four follow-up appointments. In the telehealth group, one dropped out soon after baseline, one never completed a follow-up appointment but was enrolled for all 3 months; two only had one follow-up visit. In the UC group, one dropped out after baseline, two were kept in the study for the 3-month duration but were lost to followup; one missed only the 3-month follow-up because he exited the study due to incarceration. Compared to completers, the eight veterans that dropped out before the end of the study had lower CDRS scores at baseline [M = 10.0 (SD = 2.9) vs. M = 13.8 (SD = 4.1); t = 2.38; df = 23; p = .026]. There were no other differences between participants who dropped out versus participants who completed the study. Descriptive Data and Treatment Comparisons for Participant Characteristics and Outcomes The average length of inpatient stay during the initial hospitalization was M = 12.6 days (SD = 8.8). Table 1 shows descriptive data for the study sample and treatment group comparisons for baseline characteristics. This includes age, race, education, marital status, diagnosis of schizophrenia, diagnosis of schizoaffective disorder, diagnosis of alcohol dependence in the past year, diagnosis of substance (i.e., nonalcohol) dependence in the past year, and the number of individuals with a history of suicide attempts. Not displayed in Table 1 are the additional psychiatric comorbidities participants exhibited based on the MINI. There were eight participants in each group who also had a diagnosis of agoraphobia; two telehealth and one control patients also had a MINI diagnosis of social anxiety disorder. There were two participants in each group who also had a MINI diagnosis of current panic disorder; there was one participant in the telehealth group and two in the control
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TOTAL UNIQUE INPATIENT SCREENS = 1,147 NOT REFERRED BY ATTENDING MD = 54 15 Lived too far away 14 Discharged before they were able to be considered for participation 5 already participated in a similar telehealth study 2 had a history of severe adherence problems such as a substance use problem which was associated with many missed appointments 2 were being discharged to a place where the HB could not be used 5 had their initial diagnosis incorrect 1 had severe substance abuse problems 4 were not interested 3 needed long term psychiatric inpatient care 2 were facing legal charges 1 was legally incompetent
UNIQUE POSITIVE SCREENS: DIAGNOSIS OF SCHIZOPHRENIA/SCHIZOAFFECTIVE DISORDER+ RECENT SUICIDAL IDEATION OR ATTEMPT= 100
NOT ENROLLED = 15
REFERRED BY ATTENDING PSYCHIATRIST = 46
INFORMED CONSENT = 31
4 discharged prior to being approached 4 did not pass an evaluation for informed consent by a social worker 2 decided they no longer wanted to participate 1 subject signed out against medical advice 2 were not enrolled because of staffing issues 2 were found later to have had the wrong diagnosis
RANDOMIZED = 25 NOT RANDOMIZED = 6
15 Telehealth Group 10 Usual Care
4 Discharged from study • 2 signed out AMA • 1 had legal charges • 1 discharged to a place where the HB could not be used 1 was ineligible based on the SSI screening 1 withdrew because they were no longer interested
Figure 1. Recruitment flow diagram.
group also with a MINI diagnosis of obsessive compulsive disorder; there was one participant in the telehealth group also with a MINI diagnosis of posttraumatic stress disorder. As depicted in Table 1, the telehealth group had significantly lower rates of alcohol dependence. Table 1 also indicates whether or not patients received any additional treatment besides routine outpatient care. More specifically in the control group, 8 of 10 patients were discharged to routine outpatient, one went to a personal care home, and one went to the VA PRRTP. With the HB
patients, 13 were discharged to routine outpatient care, one went to a personal care home, and two went to the VA PRRTP. There were no significant differences between groups with regard to whether they received more intensive treatment. The descriptive statistics for outcomes at each time point (baseline, 2, 4, 8, and 12 weeks) by treatment groups are shown in Table 2. The Kruskal–Wallis test was used to compare continuous outcomes (SSI and CDRS) at each time point. No significant differences were found in any outcome at any time point.
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607
TABLE 2
Time-Specific Outcome by Treatment HB (N = 15) Outcome SSI
Calgary Depression Rating Scale
Baseline 2 week 4 week 8 week 12 week Baseline 2 week 4 week 8 week 12 week
UC (N = 10)
n
M
SD
Median
Range
n
M
SD
Median
Range
p value
15 13 11 11 11 15 13 11 11 11
11.0 4.8 3.8 2.0 0.9 12.5 8.3 6.9 7.2 7.3
7.0 7.7 6.2 3.4 1.7 4.8 4.6 5.9 6.1 7.0
9 0 0 0 0 12 9 8 9 4
4–29 0–22 0–15 0–10 0–5 5–21 0–16 0–18 0–17 0–18
10 7 7 7 5 10 7 7 7 6
9.6 2.0 0.7 2.4 6.2 12.8 10.9 8.9 8.1 12.0
3.3 3.7 1.5 3.5 8.2 2.9 5.7 6.3 4.6 5.9
9 0 0 1 1 14 12 13 8 12
6–16 0–10 0–4 0–8 0–19 7–17 0–17 0–14 2–17 5–21
.51 .38 .14 .80 .23 .85 .29 .52 .73 .18
Note: HB, telehealth group; UC, Usual Care group; M, mean; SD, standard deviation; SSI, Scale for Suicidal Ideation. Missing data over time were due to participant drop out, withdrawal, lost to follow up, or due to missed appointments.
HB Feasibility We calculated the average daily adherence in use of the HB system for participants. The rates of adherence were as follows: month 1: 86.9% (n = 14); month 2: 86.3% (n = 12), and month 3: 84.1% (n = 11). Intervention Effects Figure 2 shows the mean of SSI scores across time by treatment groups. Both groups showed overall improvement within the first 4 weeks. Mean SSI scores for patients in the HB group decreased over time, but the mean SSI scores for patients in the UC group initially decreased, and then increased after 4 weeks. A mixed-effect regression model was applied on the log-transformed SSI scores. A logarithm transformation was used as the data were right-skewed. The model included a linear and a quadratic term for time, an indicator variable for treatment group, an indicator for alcohol dependence, and two variables for the time by treatment group interactions which comprised the intervention effect. A significant linear time by treatment group
interaction [F(1,68) = 5.2; p < .05)] demonstrated that the HB participants had a greater improvement in SSI scores than UC participants during the 12-week study period. Results for the mixed-effect regression analyses are listed in Table 3. Figure 3 shows the mean of CDRS scores across time by treatment groups. Mean CDRS scores for patients in both the HB and the control groups decreased initially and then increased over time. A mixed-effect regression model was utilized. The final model included a linear and a quadratic term for time, a categorical variable for treatment group, an indicator for alcohol dependence, and two variables for time by treatment group interactions. No differences were found between UC and HB groups; that is, the interaction terms were not significant. Results for the mixed-effect regression analyses for depression scores are listed in Table 3.
DISCUSSION
These pilot trial findings suggest that the use of our telehealth intervention—which involved daily use of the Health Buddy© device in addition to UC—is feasible in monitoring
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12
10
SSI
8
6
UC HB
4
2
0 0
2
4
6
8
10
12
Week
Figure 2. Mean of SSI scores across time by treatment. Mean Beck Scale for Suicidal Ideation (SSI) scores. As depicted in Table 3, there was a significant interaction such that HB scores improved more than UC scores; the linear treatment interaction term yielded F(1,68) = 5.28; p < 0.05. HB, telehealth group; UC, usual care group.
TABLE 3
Adjusted Associations of Treatment Group and Continuous Outcomes Log(SSI) Parameter Treatment group Alcohol dependence Time Linear slope Quadratic trend Interaction Treatment by linear Treatment by quadratic
b (SE)
Calgary Depression Rating Scale b (SE)
F value
p value
F value
p value
0.34 (0.34) 0.58 (0.38)
0.98 2.33
.33 .13
2.24 (2.18) 1.57 (2.45)
1.05 0.41
.31 .52
0.36 (0.30) 1.33 (0.28)
1.51 22.41
.22
Telehealth Monitoring of Patients with Schizophrenia and Suicidal Ideation JOHN KASCKOW, MD, PHD, SHASHA GAO, PHD, BARBARA HANUSA, PHD, ARMANDO ROTONDI, PHD, MATTHEW CHINMAN, PHD, SUSAN ZICKMUND, PHD, JOHN GURKLIS, MD, LAUREN FOX, BS, JACK CORNELIUS, MD, IRA RICHMOND, DNP, RN, AND GRETCHEN L. HAAS, PHD
A telehealth system was developed to monitor risk following hospitalization for suicidal ideation. We hypothesized that 3 months of telehealth monitoring will result in a greater reduction in suicidal ideation. Veterans with schizophrenia admitted with recent suicidal ideation and/or a suicidal attempt were recruited into a discharge program of VA Usual Care with daily Health Buddy© monitoring (HB) or Usual Care (UC) alone. Fifteen of 25 were randomized to HB and 10 received UC. Daily adherence in the use of the HB system during months 1–3 was, respectively, 86.9%, 86.3%, and 84.1%. There were significant improvements in Beck Scale for Suicide Ideation scores in HB participants. There were no changes in depressive symptoms. Telehealth monitoring for this population of patients appears to be feasible.
Suicide is a leading cause of premature death among people with schizophrenia (Pompili et al., 2007). Suicide is also a major public health problem among veterans. Suicide rates for male and female veterans are approximately two times higher than in the general population (Blow et al., 2012; McCarthy et al., 2009). Suicide is also a leading cause of
premature death among veterans with schizophrenia. Ilgen et al. (2010) reported that veterans with schizophrenia have suicide rates of 83.3 per 100,000. Risk factors for suicide include the presence of previous attempts, an early age of onset of illness, and coexisting depressive symptoms. Patients with schizophrenia are
JOHN KASCKOW, VA Pittsburgh MIRECC, CHERP and Behavioral Health, Pittsburgh, PA, USA, and UPMC Western Psychiatric Institute and Clinic, Pittsburgh, PA, USA; SHASHA GAO, VA Pittsburgh CHERP, Pittsburgh, PA, USA; BARBARA HANUSA, VA Pittsburgh MIRECC, Pittsburgh, PA, USA; ARMANDO ROTONDI, VA Pittsburgh MIRECC, Pittsburgh, PA, USA, and UPMC Critical Care, Pittsburgh, PA, USA; MATTHEW CHINMAN, VA Pittsburgh MIRECC and CHERP, Pittsburgh, PA, USA; SUSAN ZICKMUND, VA Pittsburgh CHERP, Pittsburgh, PA, USA, and UPMC Department of Medicine, Pittsburgh, PA, USA; JOHN GURKLIS, VA Pittsburgh Behavioral Health, Pittsburgh, PA, USA; LAUREN FOX, VA Pittsburgh MIRECC, Pittsburgh, PA, USA; JACK CORNELIUS, VA Pitts-
burgh MIRECC, Pittsburgh, PA, USA, and UPMC Western Psychiatric Institute and Clinic, Pittsburgh, PA, USA; IRA RICHMOND , VA Pittsburgh Patient Care Services, Pittsburgh, PA, USA; GRETCHEN L. HAAS, VA Pittsburgh MIRECC and Behavioral Health, Pittsburgh, PA, USA, and UPMC Western Psychiatric Institute and Clinic, Pittsburgh, PA, USA. Funded by the VISN 4 MIRECC and HSRD PPO 10-249-2 (JWK). The views do not represent the views of the U.S. Department of veterans Affairs or that of the U.S. government. Address correspondence to John Kasckow, VA Pittsburgh Health Care System, University Drive C, Behavioral Health (116a), Pittsburgh, PA 15240; E-mail: [email protected]
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also more likely to commit suicide within the first few weeks or months after a hospital discharge (Cannon, Buckley, & Larkin, 1991; Desai, Dausey, & Rosenheck, 2005). Among hospitalized patients, postdischarge suicide rates are as high as 310 per 100,000 for patients with schizophrenia, with 46% of suicides occurring within the first 3 months postdischarge (Desai et al., 2005). The relationship between hospital discharge and suicide may be related to these patients experiencing a “postpsychotic depression” (Siris, 2001; Pompili, Mancinelli, & Tatarelli, 2003). It is believed that people with schizophrenia whose symptoms improve while in the hospital subsequently gain insight into their life circumstance which then appears to increase the risk for suicide after hospital discharge. Telepsychiatric interventions, which include telephone, Internet or video, show promise in providing easy-to-access services (Jennett et al., 2003). Telepsychiatry can be used as a useful way to monitor factors in individuals at risk for suicidal behavior. Worsening depressive symptoms, psychosis, and substance abuse (Hawton, Sutton, Haw, Sinclair, & Deeks, 2005) as well as the impact of early life and recent events (Pompili et al., 2011) have been cited as important risk factors. Risk factors could be monitored and addressed as indicated with telehealth systems to reduce suicide risk. Initial progress with the use of telephone-, video-, and Internet-based modalities has been made in the treatment of patients with schizophrenia (Bensink, Hailey, & Wooton, 2006; Kasckow, Felmet, et al., 2014; Rotondi, Eack, Hanusa, Spring, & Haas, 2013). The initial studies have demonstrated that the use of telehealth is feasible and in some cases has been shown to improve outcomes. One pilot study by Beebe (2001) examined the effectiveness of a telephone intervention (TIPS) for patients with schizophrenia; this intervention focused on problem solving, coping alternatives, and providing reminders to clients to use alternative coping strategies. The experimental TIPS group included 3 months of weekly telephone calls along with routine commu-
601 nity care. Compared to treatment as usual, there was a suggestion that patients in the experimental group spent more time in the community with fewer numbers of hospitalizations; however, this difference was not statistically significant. A later study by this group and others indicated that telenursing paradigms in patients with schizophrenia have been shown to enhance patient clinician communication and medication adherence (Beebe et al., 2008; Frangou, Sachpazidis, Stassinakis, & Sakas, 2005). We have developed a telehealth system for suicidal patients with schizophrenia using the Health Buddy© (Bosch Health Care, Tampa, FL, USA) system, a device that facilitates symptom assessment and patient–staff communication between outpatient visits. It is a device that is user friendly and is ideal for patients with possible cognitive impairment, including those with schizophrenia. This study involved a comparison of VA Usual Care to VA Usual Care augmented by daily use of the Health Buddy© system in a random-assignment clinical trial. We monitored both suicidal ideation and depressive symptoms as both are major risk factors for suicide in patients with schizophrenia (Hawton et al., 2005). In the trial, we tested the hypothesis that use of the telehealth system would result in a greater reduction in both suicidal ideation and depressive symptoms on standardized measures following discharge from an inpatient service, relative to a group that received only VA Usual Care. In addition, feasibility of telehealth monitoring for suicidal behavior in this population was assessed by tracking the use of the telehealth system by participants.
METHODS
Design This was a randomized clinical trial. Eligible participants were randomized to one of the two study arms: VA Usual Care (UC; control) or UC with daily Health
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Buddy© monitoring (HB; Treatment). Recruitment occurred from February 2012 to May 2013. All participants received assessments with the Beck Scale for Suicidal Ideation scores (SSI; Beck, Kovacs, & Weissman, 1979) and the Calgary Depression Rating Scale on baseline (before the Health Buddy© was installed), and at weeks 2, 4, 8, and 12 after the Health Buddy© was installed in the HB group. Sample We obtained a prescreening waiver from our internal review board (IRB) to examine medical records of veterans age 18 and older who were recently admitted. Patients’ admission records were examined to determine whether patients exhibited recent suicidal ideation or a recent suicide attempt and also whether they had a diagnosis of schizophrenia or schizoaffective disorder; if an eligible patient was found, the clinician would be asked to refer the patient. If the patient was interested, consent was obtained. Patients were further screened for the following inclusions: a Mini Mental Status score ≥21 to rule out individuals with marked cognitive impairment (Folstein, Folstein, & McHugh, 1975); lack of a medical disorder that could influence diagnostic decisions, safety, and/ or anticipated adherence so that individuals could follow through with the protocol daily; and a score >0 on items 4 or 5 on the SSI, which indicated whether the patient had active and/or passive suicidal ideation in the past week. In addition, we administered the Mini-International Neuropsychiatric Interview 6.0 (MINI) to determine whether patients had a diagnosis of schizophrenia or schizoaffective disorder (Sheehan et al., 1998). We also obtained demographic data (see Table 1). Procedures All procedures were approved by the IRB of the VA Pittsburgh Health Care System. All eligible consenting participants
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were screened initially by a nonresearch social worker to assess capacity for consent. This consisted of six questions testing knowledge about what the study involved. If participants scored 80% or higher, they were then considered for informed consent. The IRB at our institution decided that a score of 80% or higher was required. Usual Care With UC, all participants saw their clinician within 2 weeks after discharge and had their medications periodically managed by their psychiatrist or nurse practitioner. Some participants received more intensive treatment. Intensive treatment included the VA Psychosocial Residential Rehabilitation Treatment Program (PRRTP) which provides a structured and supportive residential environment (24 hr/7 days a week) as a part of the rehabilitative treatment regime for veterans with substance use disorders. In addition, participants may have stayed in a personal care home. Health Buddy© Participants in this group received UC in addition to HB monitoring. Each participant in the telehealth condition had either a wireless modem device or a Health Buddy© device connected to their landline telephone. Each day, for 10 to 15 minutes, the Health Buddy© administered a series of text-based questions that were displayed on the Health Buddy© screen called “dialogues.” The dialogues focused on monitoring symptoms of depression, psychosis, suicide, substance use, and medication adherence. Each button corresponded to a different response (e.g., “yes” vs. “no” or “this has been a problem,” “a little bit,” “sometime,” “much of the time”), and responses for each button varied with each question. Immediately after the participant responded to the dialogues, participant responses were electronically transferred to a secure website and read by nursing staff within 4 hours.
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603
TABLE 1
Baseline Characteristics by Treatment Measure Age (years) M SD Race Black White Education (in years) M SD Marital Status Married/Living with a partner Separated/Divorced/Widowed Never married Received additional treatment after discharge? (Yes) Alcohol dependence in past 12 months Substance dependence in past 12 months Schizophrenia Schizoaffective disorder Prior suicide attempts? (none vs. 1 or more)
Total (N = 25)
HB (n = 15)
UC (n = 10)
52.5 12.9
55.8 10.8
47.5 14.7
17 (68.0%) 8 (32.0%) 12.8 1.9 6 11 8 5
(24.0%) (44.0%) (32.0%) (20.0%)
9 (60.0%) 6 (40.0%)
8 (80.0%) 2 (20.0%)
p value .12
.40
12.9 2.2
12.8 1.4
.94
5 7 3 3
1 4 5 2
.22
(33.3%) (46.7%) (20.0%) (20.0%)
(10.0%) (40.0%) (50.0%) (20.0%)
>.99
6 (24.0%)
1 (6.7%)
5 (50.0%)
.02
6 (24.0%)
2 (13.3%)
4 (40.0%)
.18
13 (52.0%) 12 (48.0%) 18 (72.0%)
6 (40.0%) 9 (60.0%) 10 (66.7%)
7 (70.0%) 3 (30.0%) 8 (80.0%)
.23 .23 .66
Note: Independent samples t test was performed for continuous variables; Fisher exact test was used for categorical variables. For continuous variables, M = mean and SD = standard deviation; for categorical measures, data are expressed as N (percentages).
The HB dialogues provided daily supportive psychoeducational material. For instance, the dialogues would help participants decide when to contact their clinician when various symptoms got worse, such as psychotic symptoms (e.g., worsening guilty ideas of reference or hallucinations) or depressive symptoms (e.g., worsening sleep disturbance, depressed mood, or hopelessness). The dialogues would also provide participants contact numbers for the crisis line if they developed worsening suicidal intent and/or plan. The dialogues would monitor symptoms of substance use; for instance, if participants responded “yes” to a question inquiring as to whether they had three or more drinks within 24 hours, the dialogue would comment that this is concerning and that they should seek our help for this. The
dialogues would also encourage participants to engage in recovery focused behavior such as reaching out to friends or family members in time of need. Copies of the dialogues utilized are available upon request. The dialogues used were modified from the original ones which had been provided by Bosch Health Care (the company which markets the Health Buddy©) using patient-centered design methods as described by Nielsen (1994). As described in Kasckow, Zickmund, et al. (2014), we initially convened a panel of consumers and academic experts in suicidology, substance abuse and schizophrenia, recovery, information technology for seriously mentally ill individuals, and early warning signs of schizophrenia. Initial modifications were made based on their recommendations.
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We then recruited participants with schizophrenia or schizoaffective disorder and a history of suicidal ideation and/or suicidal attempt. With a research assistant, participants read through the dialogue scripts and commented as to whether they understood the intended meaning. Participants were also encouraged to suggest changes. The sessions were recorded and when all participants completed the testing, the recordings were subjected to a qualitative analysis. Coders derived prominent themes; these themes were discussed with the research team and final changes were made to the dialogues as described by Kasckow et al. (2014). Measures Sociodemographic information collected at baseline included age, race, education, and marital status. Dependent variables included the SSI (Beck et al., 1979) and the Calgary Depression Rating Scale scores (CDRS; Addington, Addington, & Atkinson, 1996). Assessors were not masked to intervention arm. The SSI has been used to assess suicidal ideation in various populations including those with schizophrenia and schizoaffective disorder as well as veterans (Pinninti, Steer, Rissmiller, Nelson, & Beck, 2002; Bell & Nye, 2007; Zisook et al., 2010). The SSI scale contains 21 items which are rated on a scale of 0 to 2. The maximal score is 38. Higher scores are indicative of higher levels of suicidal ideation. If an individual scores “0” on items 4 or 5, which respectively assesses active or passive suicidal ideation, then only questions 1–5, 20, and 21 are completed; questions 20 and 21, respectively, ask whether the participant had ever attempted suicide and if so, how serious the attempt was. If an individual scores >“0” on items 4 or 5 (or both), then the remaining 6–19 questions are completed. Scores from items 1– 19 are then included in the final score. Examples of the scale items from the SSI include the following. For Item 4: (0) I have no desire to kill myself, (1) I have a weak
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desire to kill myself, (2) I have a moderate to strong desire to kill myself; for Item 5: (1) I would try to save my life if I found myself in a life-threatening situation, (2) I would take a chance on life or death if I found myself in a life-threatening situation, (3) I would not take the steps necessary to avoid death if I found myself in a life-threatening situation. The CDRS has been shown to specifically assess depression in patients with schizophrenia; this scale has also been used in veteran populations (Addington, Addington, Maticka-Tyndale, & Joyce, 1992; Addington et al., 1996; Kasckow, Golshan, & Zisook 2014). The CDRS is a nine item scale; each question has a 4-point response from 0 to 3 with a maximal total score of 27. As an example, Item 7 states the following: Early Awakening: Do you wake earlier in the morning than is normal for you? How many times a week does this happen? (0) No early awakening, (1) Mild: occassionally wakes (up to twice weekly) 1 hr or more before normal time to wake or alarm time, (2) Moderate: often wakes early (up to five times weekly) 1 hr or more before normal time to wake or alarm time, (3) Severe: Often wakes 1 hr or more before normal time. As another example, item 6 states Morning Depression: When you have felt depressed over the last 2 weeks have you noticed the depression being worse at any particular time of day? (0) Absent: No depression, (1) Mild: Depression present but no diurnal variation, (2) Moderate: Depression spontaneously mentioned to be worse in a.m., (3) Severe: Depression markedly worse in a.m., with impaired functioning which improves in p.m. Analysis We calculated descriptive statistics on all study variables. Continuous measures were expressed as means and standard deviations; categorical measures were expressed by frequency and percentage. We conducted two group t test or Fisher exact tests to compare UC and HB groups on continuous and categorical sociodemographic variables, as appropriate. Outcome variables
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were compared between UC and HB groups at each time point (baseline, 2, 4, 8, and 12 weeks) using the Kruskal–Wallis test for continuous outcomes or chi-square tests for categorical outcomes. To assess feasibility, we monitored levels of daily adherence to telehealth monitoring. Adherence was defined as the percentage of days active participants downloaded responses to the questions on the HB. To test our hypotheses, we compared changes in the HB and UC groups’ SSI scores and CDRS scores at baseline, 2, 4, 8, and 12 weeks. The primary independent variable was the randomized treatment arm (HB or UC). Mixed effect regression modeling was used to examine the relationship between treatment assignment and primary outcomes. Fixed effects included time and treatment group, and their interaction. The variables that were significantly different at baseline between HB and UC groups were controlled in the model as well. The primary treatment effect examined in these models was the treatment by time interaction. The statistical significance of main effects and interactions was assessed using Wald statistics. We used orthogonal polynomials, computed via the Cholesky decomposition to avoid high correlation between original “time” scale variables, which can cause estimation problems (Narayan & Hesthaven, 2012). SAS 9.3 (SAS Institute Inc., Cary, NC, USA) was used for the analysis.
RESULTS
A total of N = 1,147 unique veterans were screened between February 2012 and May 2013 from the inpatient unit of the VA Pittsburgh Health Care System. Figure 1 depicts details of the recruiting process to the point of randomization. Of those randomized, 15 were randomized to the HB group and 10 were randomized to UC. Fourteen of 15 participants could set up the system and report their symptoms through the system. Thirteen (86.7%) of the HB and 7 (70.0%) of the UC group
605 completed at least one follow-up interview. Overall, 11 (73.3%) of the HB group and 6 (60.0%) of the UC group completed all four follow-up appointments. In the telehealth group, one dropped out soon after baseline, one never completed a follow-up appointment but was enrolled for all 3 months; two only had one follow-up visit. In the UC group, one dropped out after baseline, two were kept in the study for the 3-month duration but were lost to followup; one missed only the 3-month follow-up because he exited the study due to incarceration. Compared to completers, the eight veterans that dropped out before the end of the study had lower CDRS scores at baseline [M = 10.0 (SD = 2.9) vs. M = 13.8 (SD = 4.1); t = 2.38; df = 23; p = .026]. There were no other differences between participants who dropped out versus participants who completed the study. Descriptive Data and Treatment Comparisons for Participant Characteristics and Outcomes The average length of inpatient stay during the initial hospitalization was M = 12.6 days (SD = 8.8). Table 1 shows descriptive data for the study sample and treatment group comparisons for baseline characteristics. This includes age, race, education, marital status, diagnosis of schizophrenia, diagnosis of schizoaffective disorder, diagnosis of alcohol dependence in the past year, diagnosis of substance (i.e., nonalcohol) dependence in the past year, and the number of individuals with a history of suicide attempts. Not displayed in Table 1 are the additional psychiatric comorbidities participants exhibited based on the MINI. There were eight participants in each group who also had a diagnosis of agoraphobia; two telehealth and one control patients also had a MINI diagnosis of social anxiety disorder. There were two participants in each group who also had a MINI diagnosis of current panic disorder; there was one participant in the telehealth group and two in the control
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TOTAL UNIQUE INPATIENT SCREENS = 1,147 NOT REFERRED BY ATTENDING MD = 54 15 Lived too far away 14 Discharged before they were able to be considered for participation 5 already participated in a similar telehealth study 2 had a history of severe adherence problems such as a substance use problem which was associated with many missed appointments 2 were being discharged to a place where the HB could not be used 5 had their initial diagnosis incorrect 1 had severe substance abuse problems 4 were not interested 3 needed long term psychiatric inpatient care 2 were facing legal charges 1 was legally incompetent
UNIQUE POSITIVE SCREENS: DIAGNOSIS OF SCHIZOPHRENIA/SCHIZOAFFECTIVE DISORDER+ RECENT SUICIDAL IDEATION OR ATTEMPT= 100
NOT ENROLLED = 15
REFERRED BY ATTENDING PSYCHIATRIST = 46
INFORMED CONSENT = 31
4 discharged prior to being approached 4 did not pass an evaluation for informed consent by a social worker 2 decided they no longer wanted to participate 1 subject signed out against medical advice 2 were not enrolled because of staffing issues 2 were found later to have had the wrong diagnosis
RANDOMIZED = 25 NOT RANDOMIZED = 6
15 Telehealth Group 10 Usual Care
4 Discharged from study • 2 signed out AMA • 1 had legal charges • 1 discharged to a place where the HB could not be used 1 was ineligible based on the SSI screening 1 withdrew because they were no longer interested
Figure 1. Recruitment flow diagram.
group also with a MINI diagnosis of obsessive compulsive disorder; there was one participant in the telehealth group also with a MINI diagnosis of posttraumatic stress disorder. As depicted in Table 1, the telehealth group had significantly lower rates of alcohol dependence. Table 1 also indicates whether or not patients received any additional treatment besides routine outpatient care. More specifically in the control group, 8 of 10 patients were discharged to routine outpatient, one went to a personal care home, and one went to the VA PRRTP. With the HB
patients, 13 were discharged to routine outpatient care, one went to a personal care home, and two went to the VA PRRTP. There were no significant differences between groups with regard to whether they received more intensive treatment. The descriptive statistics for outcomes at each time point (baseline, 2, 4, 8, and 12 weeks) by treatment groups are shown in Table 2. The Kruskal–Wallis test was used to compare continuous outcomes (SSI and CDRS) at each time point. No significant differences were found in any outcome at any time point.
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607
TABLE 2
Time-Specific Outcome by Treatment HB (N = 15) Outcome SSI
Calgary Depression Rating Scale
Baseline 2 week 4 week 8 week 12 week Baseline 2 week 4 week 8 week 12 week
UC (N = 10)
n
M
SD
Median
Range
n
M
SD
Median
Range
p value
15 13 11 11 11 15 13 11 11 11
11.0 4.8 3.8 2.0 0.9 12.5 8.3 6.9 7.2 7.3
7.0 7.7 6.2 3.4 1.7 4.8 4.6 5.9 6.1 7.0
9 0 0 0 0 12 9 8 9 4
4–29 0–22 0–15 0–10 0–5 5–21 0–16 0–18 0–17 0–18
10 7 7 7 5 10 7 7 7 6
9.6 2.0 0.7 2.4 6.2 12.8 10.9 8.9 8.1 12.0
3.3 3.7 1.5 3.5 8.2 2.9 5.7 6.3 4.6 5.9
9 0 0 1 1 14 12 13 8 12
6–16 0–10 0–4 0–8 0–19 7–17 0–17 0–14 2–17 5–21
.51 .38 .14 .80 .23 .85 .29 .52 .73 .18
Note: HB, telehealth group; UC, Usual Care group; M, mean; SD, standard deviation; SSI, Scale for Suicidal Ideation. Missing data over time were due to participant drop out, withdrawal, lost to follow up, or due to missed appointments.
HB Feasibility We calculated the average daily adherence in use of the HB system for participants. The rates of adherence were as follows: month 1: 86.9% (n = 14); month 2: 86.3% (n = 12), and month 3: 84.1% (n = 11). Intervention Effects Figure 2 shows the mean of SSI scores across time by treatment groups. Both groups showed overall improvement within the first 4 weeks. Mean SSI scores for patients in the HB group decreased over time, but the mean SSI scores for patients in the UC group initially decreased, and then increased after 4 weeks. A mixed-effect regression model was applied on the log-transformed SSI scores. A logarithm transformation was used as the data were right-skewed. The model included a linear and a quadratic term for time, an indicator variable for treatment group, an indicator for alcohol dependence, and two variables for the time by treatment group interactions which comprised the intervention effect. A significant linear time by treatment group
interaction [F(1,68) = 5.2; p < .05)] demonstrated that the HB participants had a greater improvement in SSI scores than UC participants during the 12-week study period. Results for the mixed-effect regression analyses are listed in Table 3. Figure 3 shows the mean of CDRS scores across time by treatment groups. Mean CDRS scores for patients in both the HB and the control groups decreased initially and then increased over time. A mixed-effect regression model was utilized. The final model included a linear and a quadratic term for time, a categorical variable for treatment group, an indicator for alcohol dependence, and two variables for time by treatment group interactions. No differences were found between UC and HB groups; that is, the interaction terms were not significant. Results for the mixed-effect regression analyses for depression scores are listed in Table 3.
DISCUSSION
These pilot trial findings suggest that the use of our telehealth intervention—which involved daily use of the Health Buddy© device in addition to UC—is feasible in monitoring
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12
10
SSI
8
6
UC HB
4
2
0 0
2
4
6
8
10
12
Week
Figure 2. Mean of SSI scores across time by treatment. Mean Beck Scale for Suicidal Ideation (SSI) scores. As depicted in Table 3, there was a significant interaction such that HB scores improved more than UC scores; the linear treatment interaction term yielded F(1,68) = 5.28; p < 0.05. HB, telehealth group; UC, usual care group.
TABLE 3
Adjusted Associations of Treatment Group and Continuous Outcomes Log(SSI) Parameter Treatment group Alcohol dependence Time Linear slope Quadratic trend Interaction Treatment by linear Treatment by quadratic
b (SE)
Calgary Depression Rating Scale b (SE)
F value
p value
F value
p value
0.34 (0.34) 0.58 (0.38)
0.98 2.33
.33 .13
2.24 (2.18) 1.57 (2.45)
1.05 0.41
.31 .52
0.36 (0.30) 1.33 (0.28)
1.51 22.41
.22
