Abstract
Background:
Caregivers are decision stakeholders; yet, few interventions have been developed to help patients and caregivers collaborate on advance care planning (ACP).
Objective:
To evaluate a theory-based ACP pilot intervention, Deciding Together, to improve decisional quality, readiness, collaboration, and concordance in ACP decisions for older adult home health (HH) patients and caregivers.
Design:
A one-group, pre- and posttest study using matched questionnaires was conducted. The intervention consisted of a clinical vignette, theoretically guided conversation prompts, and a shared decision-making activity.
Setting/Subjects:
N = 36 participants (n = 18 HH patients; n = 18 family and nonfamily caregivers) were purposively recruited from a HH agency to participate in the intervention at patients' homes.
Measurements:
Demographic and baseline measures were collected for relationship quality, health status, and previous ACP engagement. Outcome measures included perceptions of collaboration, readiness for ACP, concordance in life-sustaining treatment preferences (cardiopulmonary resuscitation, antibiotics, artificial nutrition and hydration, and mechanical ventilation), and decisional conflict. Descriptive statistics, Cohen's κ coefficients, paired t tests, McNemar's tests, and Wilcoxon signed-rank tests (and effect size estimates, r = z/√N) were calculated using R-3.5.1 (p < 0.05). Single value imputation was used for missing values.
Results:
While no significant differences were found for perceptions of collaboration, and readiness for ACP, patients (r = 0.38, p = 0.02) and caregivers (r = 0.38, p = 0.02) had reduced decisional conflict at posttest. Patients' and caregivers' agreement increased by 27.7% for an item assessing patients' preference for artificial nutrition and hydration (p = 0.03).
Conclusions:
This study suggests that collaborative ACP decision making may improve decisional conflict for older adult HH patients and their caregivers.
Keywords: advance care planning, caregivers, communication, home care services, shared decision making
Introduction
The home health (HH) patient population is more frail, homebound, and functionally impaired than the general population.1 HH patients have high rates of emergency department visits and inpatient hospitalizations, for which having advance care planning (ACP) would be useful. However, a nationwide survey of long-term care providers found that long-term HH patients had the lowest rate (28%) of documented advance directives compared with patients utilizing other long-term care services (65% nursing home, 88% hospice).2
Caregivers for patients with chronic illness such as HH patients are often involved in hands-on caregiving and medical decision making,3 and are directly and indirectly affected by patients' illness and treatment consequences. ACP communication has been associated with more appropriate care and improved quality of life for patients and improved bereavement outcomes for caregivers engaged in decision making.4–7 Engaging caregivers in ACP decisions may also foster preparedness and may prevent ethical issues in which surrogate decision makers over-ride patients' end-of-life wishes due to a lack of understanding or agreement.8
When patients with chronic illness and caregivers cope with illness together, they experience greater support, relationship quality, and reduced depressive symptoms.9–11 Open ACP discussions are associated with better death preparedness, improved decision concordance, and stronger relationships between patients and surrogates.12–15 In contrast, difficulty in ACP communication can hinder caregivers' engagement in ACP decisions.16 A recent intervention study promoting consensus in advance directive completion among patient–caregiver dyads found that joint completion of advance directives improved decisional concordance for patient–caregiver dyad, supporting the applicability of a collaborative approach to ACP.17
Surrogates need to be prepared to enact patients' important medical decisions; however, even designated health care proxies have reported inadequate readiness for surrogate decision making.18 Patients' and caregivers' unequal readiness for ACP can cause conflict in shared decision making.19 Approximately half of caregivers experience moderate-to-severe conflict about enacting decisions for critically ill patients,20 underscoring the importance of readiness in surrogate decision making.
ACP decisions can be stressful, and have individual and dyadic consequences for patients and caregivers. While encouraging collaboration and mutual support may help patients and caregivers make more meaningful shared ACP decisions, there are few theory-led dyadic interventions designed for collaborative ACP decisions. The developmental contextual model (DCM) of dyadic coping developed by Berg and Upchurch21 extended the dyadic applications of stress and coping theory to the context of chronic illness in married/romantic relationships. The DCM posits that dyads appraise stressors, cope positively or negatively, and respond adaptively or maladaptively as a unit throughout the trajectory of illness.21 Couples who exhibit positive dyadic coping have been shown to have lower cancer-related stress and more positive day-to-day mood,9,10 while those with lower dyadic coping are more likely to have poorer quality of life.22 While the DCM has been applied successfully to examine decision making among patients with dementia and their family members for day-to-day care decisions,23 no studies have applied the DCM to enhance collaborative ACP decisions.
The Deciding Together intervention
The Deciding Together intervention was tested and refined in a previous feasibility study. Deciding Together encouraged patient–caregiver dyads to reflect on past and present medical decision making, and examine how medical decisions have shared consequences. During the intervention, a shared stressor (a decision to continue or withdraw life-sustaining treatments) was introduced through a clinical vignette where the patient developed sepsis in the intensive care unit. Participants were encouraged to think about consequences for the other person when deciding about continuing or withdrawing life-sustaining treatments (cardiopulmonary resuscitation, mechanical ventilation, antibiotics, and artificial nutrition and hydration). To encourage mutual support and open communication, participants were instructed to talk to each other and use positive communication techniques such as active listening and open sharing. Finally, dyads were guided to think about collaborating on future ACP decisions and were given five minutes to complete a page of an advance directive together without external help (Supplementary Data).
Study purpose
This study sought to evaluate the effect of Deciding Together on improving collaboration, decisional quality, and readiness for ACP among older adult HH patients and their caregivers. The hypotheses were that Deciding Together would be positively associated with (1) perceptions of collaborative decision making, (2) ACP decisional quality (improved decision concordance and reduced decisional conflict), and (3) readiness for ACP.
Materials and Methods
Design
This one-group, pre- and posttest pilot study was approved by the University Institutional Review Board in December 2017. Purposive recruitment was conducted at a large HH agency in Utah to recruit from two of the most populated counties in the state.
Setting/subjects
Eligible patients were ≥55 years, had at least one chronic condition, English speaking, and cognitively and physically able to complete the study. Patients were asked to nominate one caregiver whom they preferred as study partners even if they had multiple caregivers. Study relationship was documented during screening. Eligible caregivers were relatives or friends ≥18 years, English speaking, and involved in medical decisions with patients (e.g., information gathering, advice, etc.). Current patients and those who had HH services in the past six months were identified through chart review and were mailed a recruitment letter. Those who did not opt out were contacted by phone. Care managers were also encouraged to refer potential participants for the study. The overall response rate was 13.64% (Fig. 1). Homogeneity tests showed that current and past patients were similar in age, functional status, and proportions of previously completed ACP activities (p > 0.05).
FIG. 1.
Study recruitment response. RR, response rate.
Study procedures
Informed consent was obtained from participants after a cognitive screen with the Short Portable Mental Status Questionnaire—participants with three or more errors were ineligible.24 Matched pre- and posttest baseline questionnaires were independently completed by patients and caregivers. Participants were presented the vignette; then they were asked about their treatment preferences, decisional conflict, and decisional control preferences. Caregivers were asked to predict patients' treatment preferences. Dyads were then video-recorded during the Deciding Together intervention (Supplementary Data), which was administered by the first author. After the intervention, participants individually completed posttest questionnaires, were debriefed, and reimbursed with a $50 gift card.
Intervention fidelity
Study procedures were manualized using a checklist. The interventionist (D.L.T.) utilized scripted instructions, limited conversation prompts, and kept to outlined time frames. Four randomly selected recordings were reviewed by a member of the research team (L.E.). Protocol adherence, interventionist competence, and participant response were monitored. The recordings ranged from 10 to 41 minutes in length. Adherence to the manual was high among the reviewed recordings (n = 27.75/28 adherence items, 98.2%, standard deviation [SD] = 0.5).
Variables
Baseline measures
Baseline measures included participants' demographic characteristics, Patient-Reported Outcomes Measurement Information System Global Health Survey v1.2 (10-item, Physical Health subscale α = 0.81; Mental Health subscale α = 0.86),25 the four-item Couple's satisfaction index (α = 0.94),26 and a modified one-item Control Preferences Scale question.27 While patients' functional dependence on study caregivers was not assessed, patients' functional dependence was documented during chart review.
Outcome measures
The main outcome of collaboration was assessed with the Perceptions of Collaboration Questionnaire (PCQ), a nine-item self-reported questionnaire assessing perceived cognitive compensation, interpersonal enjoyment, and frequency of everyday decision making in relation with study partners (α = 0.57–0.80).28
Secondary measures included decisional quality and readiness for ACP (R-ACP). Decisional quality was operationalized as decision concordance between patients' preferences and caregivers' prediction of patients' preference and decisional conflict. Decision concordance was measured with Cohen's κ coefficients for the goals of care question: “If you had to make a choice for the future in this situation, would you: 1) preserve life as long as possible despite more pain and discomfort, 2) relieve pain and discomfort as much as possible despite limiting life, 3) not sure, or 4) other?”29 (consolidated to 1 = life prolongation at all costs, 2 = prevent pain at all costs, and 3 = other).
Kappa coefficients assessed agreement between patients' preferences and caregivers' prediction of patients' preferences for four life-sustaining treatments.30 Participants indicated if they definitely or probably did not want the treatment, definitely or probably wanted the treatment, or if they were unsure (consolidated to 1 = not preferred, 2 = preferred, and 3 = unsure to assess items as categorical variables).
Decisional conflict was measured by the 16-item, 5-point Likert style Decisional Conflict Scale (DCS).31 Items were scored and transformed to a scale of 0–100. The scale consists of five subscales (Informed Decision, Values, Support, Uncertainty, and Effective Decision) and has Cronbach's α of 0.78.31
The four-item R-ACP scale was used to assess participants' readiness to talk with the study partner and doctor regarding preferred end-of-life care, legally document wishes, and assign a health care proxy (α = 0.86).32
Statistical analyses
All analyses were conducted in R-3.5.1. Descriptive statistics and unweighted Cohen's κ coefficients were produced. Data were assessed for normality with the Shapiro–Wilk's test. Paired t tests and Wilcoxon signed-rank tests were used to examine pre- to posttest differences in outcome measures. Full agreement or no agreement for the goals of care and each of the four life-sustaining treatments was assessed with McNemar's tests. Bonferroni adjustments were conducted for subscale tests when outcome measures were significant. Missing data were examined with Little's MCAR test. Despite low proportions of missing data (5.6%–17.0%), single imputation using a tree-based approach was conducted using the missForest package and imputed values were used. This study was powered to detect a large effect size (Cohen's d = 0.8) at the p < 0.05 with a two-tailed paired t test powered at 80%.
Results
Eighteen dyads (N = 36) were recruited, consisting of spousal, parent–child, friend, and nonspousal/parental relative (cousin, sister) dyads. All caregivers were either primary caregivers or were significant sources of social support for patients. The majority of participants were female (patients = 61.11%; caregivers = 72.22%), married (patients = 55.56%; caregivers = 66.67%), white (patients = 100.00%; caregivers = 100.00%), non-Hispanic (patients = 100.00%; caregivers = 93.75%), had less than a bachelor's degree (patients = 88.89%; caregivers = 83.33%), and had an annual household income of <$50,000 (patients = 80.00%; caregivers = 72.22%). Ambulation was the most common functional limitation of patients (most had one limitation at the time of chart review). Over three-quarters of participants self-reported completing at least one type of ACP (i.e., having an advance directive, health care proxy, provider order for life-sustaining treatment, or do-not-resuscitate order; Table 1).
Table 1.
Baseline Participant Characteristics for Categorical Variables (N = 36)
| Variable | Patients (n = 18), n (%) | Caregivers (n = 18), n (%) |
|---|---|---|
| Gender | ||
| Male | 7 (38.89) | 5 (27.78) |
| Female | 11 (61.11) | 13 (72.22) |
| Marital status | ||
| Married | 10 (55.56) | 12 (66.67) |
| Divorced | 3 (16.67) | 5 (27.78) |
| Widowed | 4 (22.22) | 1 (5.56) |
| Single/never married | 1 (5.56) | 0 (0.00) |
| Nature of relationship | ||
| Spousal | 9 (50.00) | — |
| Parent–child | 4 (22.22) | — |
| Close friends | 3 (16.67) | — |
| Nonspousal family members | 2 (11.11) | — |
| Racea | ||
| White | 18 (100.00) | 16 (100.00) |
| Ethnicitya | ||
| Hispanic/Latino | 0 (0.00) | 1 (6.25) |
| Non-Hispanic/Latino | 17 (100.00) | 15 (93.75) |
| Religion | ||
| Protestant | 6 (33.33) | 3 (16.67) |
| Latter day saint | 10 (55.56) | 9 (50.00) |
| Catholic | 1 (5.56) | 2 (11.11) |
| No religion | 1 (5.56) | 4 (22.22) |
| Level of spirituality | ||
| Highly religious/spiritual | 8 (44.44) | 10 (55.56) |
| Somewhat religious/spiritual | 8 (44.44) | 5 (27.78) |
| Not very religious/spiritual | 0 (0.00) | 2 (11.11) |
| Not at all religious/spiritual | 2 (11.11) | 1 (5.56) |
| Educational level | ||
| High school/GED | 6 (33.33) | 6 (33.33) |
| Some college or more | 5 (27.78) | 7 (38.89) |
| Associate's degree or more | 5 (27.78) | 2 (11.11) |
| Bachelor's degree or more | 2 (11.11) | 1 (5.56) |
| Advanced degree | 0 (0.00) | 2 (11.11) |
| Incomea | ||
| <$25,000 | 6 (40.00) | 6 (33.33) |
| $25,000–<$50,000 | 6 (40.00) | 7 (38.89) |
| $50,000–<$75,000 | 2 (13.33) | 2 (11.11) |
| ≥$75,000 | 1 (6.67) | 3 (16.67) |
| Knowing anyone with terminal illness or coma in past five years | ||
| Yes | 10 (55.56) | 13 (72.22) |
| No | 8 (44.44) | 5 (27.78) |
| Cognitive functioning (SPMSQ) | ||
| 0 errors | 9 (50.00) | 12 (66.67) |
| 1 error | 6 (33.33) | 5 (27.78) |
| 2 errors | 3 (16.67) | 1 (5.56) |
| Self-reported previous ED visit in past 12 months | ||
| 0 visits | 5 (27.78) | — |
| 1–2 visits | 4 (50.00) | — |
| ≥3 visits | 9 (22.22) | — |
| Self-reported previous inpatient stays in the past 12 months | ||
| 0 inpatient stays | 3 (16.67) | — |
| 1–2 inpatient stays | 15 (83.33) | — |
| Patient diagnoses | ||
| Neoplasms | 2 (11.11) | — |
| Blood and immune disorders | 1 (5.55) | — |
| Endocrine, nutritional, and metabolic diseases | 8 (44.44) | — |
| Mental, behavioral, and neurodevelopmental disorders | 2 (11.11) | — |
| Diseases of the nervous system | 6 (33.33) | — |
| Diseases of the circulatory system | 7 (38.89) | — |
| Diseases of the respiratory system | 5 (27.78) | — |
| Diseases of the digestive system | 3 (16.67) | — |
| Diseases of the skin and subcutaneous tissue | 2 (11.11) | — |
| Diseases of the musculoskeletal system and connective tissue | 10 (55.56) | — |
| Diseases of the genitourinary system | 4 (22.22) | — |
| Patients' functional limitations | ||
| Bathing | 6 (33.33) | — |
| Transfers | 7 (38.89) | — |
| Ambulation | 16 (88.89) | — |
| Dressing or grooming | 8 (44.44) | — |
| Toileting | 6 (33.33) | — |
| Self-recall patients' previous ACP | ||
| Previous AD, HCP, POLST, or DNR | 14 (77.78) | 13 (72.22) |
| No AD, HCP, POLST, or DNR | 4 (22.22) | 5 (27.78) |
| Control preferences for ACP | ||
| Patient takes more active role | 11 (61.11) | 9 (50.00) |
| Patient–study partner collaborative roles | 6 (33.33) | 8 (44.44) |
| Study partner takes more active role | 1 (5.56) | 1 (5.56) |
Indicates missing values.
ACP, advance care planning; AD, advance directives; DNR, do-not-resuscitate order; ED, emergency department; GED, general educational development; HCP, health care proxy; POLST, provider order for life-sustaining treatment; SPMSQ, Short Portable Mental Status Questionnaire.
Patients were slightly older than caregivers (patients: 68.22 years, SD = 9.64; caregivers: 61.28 years, SD = 13.60) and were similar in baseline R-ACP and decisional conflict. Patients reported significantly poorer overall health (mean [M] = 31.41, SD = 7.95) and higher interdependence with caregivers for collaboration related to cognitive compensation (M = 12.61, SD = 2.06) during everyday decision making compared with caregivers (Table 2).
Table 2.
Comparison of Baseline Participant Characteristics for Continuous Variables (N = 36)
| Variable | Patients (n = 18) |
Caregivers (n = 18) |
p* | ||
|---|---|---|---|---|---|
| Mean (SD) | Min–Max | Mean (SD) | Min–Max | ||
| Age | 68.22 (9.64) | 55–88 | 61.28 (13.60) | 36–81 | 0.07 |
| Relationship quality (CSI)a | 16.47 (2.85) | 12–21 | 15.67 (3.87) | 6–20 | 0.35 |
| Health status (PROMIS)a | 31.41 (7.95) | 17–47 | 35.31 (6.17) | 23–45 | 0.04 |
| Physical health | 12.29 (3.39) | 6–18 | 14.19 (2.54) | 9–18 | 0.15** |
| Mental health | 13.28 (3.36) | 8–20 | 13.71 (3.74) | 7–19 | 1.00** |
| PCQa | 36.33 (4.70) | 27–45 | 33.12 (5.23) | 23–41 | 0.02 |
| Cognitive compensation | 12.61 (2.06) | 9–15 | 10.56 (2.57) | 7–15 | 0.03** |
| Frequency | 11.17 (1.95) | 9–15 | 10.75 (2.21) | 6–15 | 1.00** |
| Enjoyment | 12.56 (1.82) | 9–15 | 12.28 (1.74) | 8–15 | 1.00** |
| R-ACP | 16.50 (5.04) | 5–20 | 14.39 (6.42) | 4–20 | 0.24 |
| DCSa | 16.93 (12.54) | 0.00–42.19 | 20.94 (14.40) | 0.00–45.31 | 0.21 |
Bolded values indicate significance at p < 0.05.
Normally distributed variables were assessed with paired t tests; non-normally distributed variables were assessed with Wilcoxon signed-rank tests.
p-Values adjusted with Bonferroni correction.
Indicates missing values.
CSI, Couples Satisfaction Index; DCS, Decisional Conflict Scale; Max, maximum; Min, minimum; PCQ, Perceptions of Collaboration Questionnaire; PROMIS, Patient-Reported Outcomes Measurement Information System; R-ACP, Readiness for ACP; SD, standard deviation.
Primary outcome-PCQ
We hypothesized that Deciding Together would improve dyads' PCQ scores. However, there were no significant differences for participants in PCQ at posttest (patients: p = 0.59; caregivers: p = 0.32).
Secondary outcomes-decisional quality (decisional conflict and concordance)
Decisional conflict
Participants improved in decisional conflict (Table 3). Patients' median DCS score at pretest was 22.66 and 9.38 at posttest (p = 0.02, r = 0.38), while caregivers' median DCS score was 22.66 at pretest and 9.38 at posttest (p = 0.02, r = 0.38). At pretest, patients' median uncertainty score was 25.00, while posttest uncertainty score was 4.17 (p = 0.02, r = 0.44). For caregivers, median scores for the Effective Decision subscale improved from 25.00 at pretest to 15.62 at posttest (p = 0.01, r = 0.49).
Table 3.
Pre- and Posttest Differences in Outcome Measures for Patients and Caregivers
| Variable | Patient (n = 18) |
Caregivers (n = 18) |
||||||
|---|---|---|---|---|---|---|---|---|
| Pretest mean (SD) | Posttest mean (SD) | p* | Effect size (r) | Pretest mean (SD) | Posttest mean (SD) | p* | Effect size (r) | |
| R-ACP | 16.5 (5.04) | 16.78 (4.52) | 0.25 | — | 14.39 (6.42) | 15.67 (5.04) | 0.07 | — |
| PCQa | 36.33 (4.70) | 36.89 (4.17) | 0.49 | — | 33.54 (5.07) | — | 0.32 | — |
| Cognitive compensation | 12.61 (2.06) | 12.83 (2.01) | — | — | 10.56 (2.57) | 10.44 (2.2) | — | — |
| Frequency | 11.17 (1.95) | 11.33 (1.50) | — | — | 10.94 (2.14) | 11.50 (2.04) | — | — |
| Enjoyment | 12.56 (1.82) | 12.72 (1.49) | — | — | 12.28 (1.74) | 12.56 (1.46) | — | — |
| DCSa | 16.93 (12.54) | 11.89 (11.62) | 0.02 | 0.38 | 20.60 (14.06) | 15.16 (12.40) | <0.01 | 0.46 |
| Median = 22.66 | Median = 9.38 | Median = 23.44 | Median = 11.72 | |||||
| Informed decision | 17.59 (13.06) | 15.74 (12.75) | — | — | 17.12 (14.98) | 13.43 (13.45) | — | — |
| Median = 25.00 | Median = 20.83 | Median = 20.56 | Median = 16.67 | |||||
| Values | 18.06 (14.92) | 13.43 (14.61) | — | — | 18.98 (16.37) | 13.89 (15.39) | — | — |
| Median = 25.00 | Median = 12.50 | Median = 25.00 | Median = 8.33 | |||||
| Support | 13.89 (12.46) | 8.33 (11.43) | 0.42** | — | 20.37 (12.20) | 16.25 (14.46) | 0.56** | — |
| Median = 16.67 | Median = 0.00 | Median = 25.00 | Median = 16.67 | |||||
| Uncertainty | 19.91 (16.7) | 10.65 (13.65) | 0.02** | 0.44 | 26.91 (22.35) | 18.52 (12.31) | 0.05** | — |
| Median = 25.00 | Median = 4.17 | Median = 25.00 | Median = 25.00 | |||||
| Effective decision | 15.62 (13.43) | 11.46 (13.26) | 0.21** | — | 22.22 (16.77) | 13.89 (13.65) | 0.01** | 0.49 |
| Median = 21.88 | Median = 3.12 | Median = 25.00 | Median = 15.62 | |||||
Bolded values indicate statistical significance at the p < level (unadjusted).
Normally distributed variables were assessed with paired t tests; non-normally distributed variables were assessed with Wilcoxon signed-rank tests.
Bonferroni adjusted p-value.
Missing values were imputed using the missForest package in R.
Decisional concordance
At baseline, caregivers correctly predicted patients' preferences for their goals of care 61.1% of the time (k = 0.21, 95% confidence interval [CI] = −0.17 to 0.60; Table 4). Baseline concordance for specific life-sustaining treatment preferences ranged from k = 0.12 to k = 0.42, and ranged between k = 0.14 to k = 0.89 at posttest. Only dyadic concordance for artificial nutrition and hydration significantly improved at posttest (pretest: k = 0.42, 95% CI = 0.11–0.73, posttest: k = 0.89, 95% CI = 0.67–1.00, p = 0.03).
Table 4.
Concordance Between Patients and Caregivers Life-Sustaining Treatment Decisions at Pretest and Posttest
| Pretest |
Posttest |
p | |||||
|---|---|---|---|---|---|---|---|
| Agreement (%) | κ | 95% CI | Agreement (%) | κ | 95% CI | ||
| Goals of care | 61.1 | 0.213 | −0.17 to 0.6 | 61.1 | 0.319 | −0.03 to 0.67 | 1.00 |
| Life-sustaining treatments | |||||||
| CPRa | 66.7 | 0.28 | −0.10 to 0.66 | 61.1 | 0.143 | −0.28 to 0.57 | 0.65 |
| ABXa | 50 | 0.182 | −0.13 to 0.50 | 72.2 | 0.511 | 0.20 to 0.82 | 0.16 |
| ANH | 66.7 | 0.419 | 0.11 to 0.73 | 94.4 | 0.885 | 0.67 to 1.00 | 0.03 |
| MVa | 50 | 0.12 | −0.23 to 0.47 | 72.2 | 0.467 | 0.12 to 0.82 | 0.10 |
Bolded values indicate statistical significance at the p < level.
Variables with missing values were imputed using the missForest package in R.
ABX, antibiotics; ANH, artificial nutrition and hydration; CI, confidence interval; CPR, cardiopulmonary resuscitation; MV, mechanical ventilation.
Readiness for ACP
R-ACP scores showed no significant improvement. However, posttest scores for caregivers trended toward significance (p = 0.0.07; Table 3).
Secondary analysis accounting for previous completion of ACP
To assess for the possibility that results were affected by the high rate of previous ACP engagement in the sample, a secondary analysis of outcome measures was conducted with multivariable regression models.
While patients' pretest R-ACP (B = 0.36, p = 0.01) and previous ACP (B = 6.35, p < 0.01) were positively associated with posttest R-ACP, only caregivers' pretest R-ACP (B = 0.61, p < 0.01) was associated with increases in R-ACP at posttest. Previous completion of ACP was not associated with posttest increases in PCQ, decisional conflict, or concordance (p > 0.05; Table 5).
Table 5.
Secondary Analyses Examining the Effect of Any Previous Advance Care Planning Completion on Outcome Measures
| Outcome measuresa | Patients (n = 18) |
Caregivers (n = 18) |
||||
|---|---|---|---|---|---|---|
| B | p | Adjusted R2 | B | p | Adjusted R2 | |
| R-ACP (intercept) | 5.85 | <0.01 | 0.81 | 4.93 | <0.01 | 0.86 |
| Pretest R-ACP | 0.36 | 0.01 | 0.61 | 0.01 | ||
| Any ACP | 6.35 | <0.01 | 2.50 | 0.11 | ||
| PCQ (intercept) | 18.69 | 0.03 | 0.41 | 14.89 | <0.05 | 0.44 |
| Pretest PCQ | 0.52 | 0.02 | 0.55 | <0.01 | ||
| Any ACP | −2.16 | 0.37 | 0.45 | 0.84 | ||
| DCS | −2.05 | 0.65 | 0.55 | 0.06 | 1.00 | 0.66 |
| Pretest DCS | 0.70 | <0.01 | 0.74 | <0.01 | ||
| Any ACP | 2.66 | 0.56 | 0.13 | 0.98 | ||
Bolded values indicate significance at p < 0.05.
The relationships between any previous ACP completion and absolute agreement between patients and caregivers for goals of care and life-sustaining treatment preferences were assessed with Fisher's exact test for count data. Previous ACP completion was not associated with agreement at pre- or posttest.
Discussion
Older adult HH patients tend to have a higher level of dependency on caregivers, more complex health conditions, and higher medical utilization, making collaboration on ACP highly relevant.1,2 The majority of shared decision-making interventions for ACP are focused on the patient–provider dyad with very few targeting patients and caregivers.33 To our knowledge, this is the first DCM-based intervention designed to improve collaboration between patients and caregivers for ACP decision making.
Perceptions of Collaboration Questionnaire
Despite our hypothesis, the Deciding Together intervention did not improve PCQ scores, possibly because baseline scores were already high. Future studies should evaluate if increasing the difficulty of decision making presented in the vignette increases collaboration among dyads due to the need for greater collaborative problem solving. Moreover, dyads may have already discussed treatment decisions presented in the vignette, which is suggested by the high rate of ACP. As ACP consists of several types of activities including designating a health care proxy, the patient–caregiver dyadic design of the study may have contributed to the high ACP rate in the sample. Follow-up studies with a larger and more heterogeneous sample are recommended.
Decisional quality concordance
At baseline, dyads agreed on patients' overall goals for care decision 61.1% (k = 0.21) of the time, slightly lower than a widely cited 2006 meta-analysis, which reported that patients and surrogates agree 68% of the time on end-of-life preferences.34 Baseline concordance for treatment decisions ranged from k = 0.12–0.42, suggesting that more detailed discussions with patients about their preferences are needed. Similar to another study, concordance for mechanical ventilation preferences was poorest at baseline,17 suggesting that discussion and education about the consequences of these treatments and how they relate to overall goals of care are needed.
However, the vignette and shared appraisals in Deciding Together may have allowed for dyads to engage in deeper discussion and clarification of physical and emotional consequences of specific types of treatment decisions. We found that concordance for artificial nutrition and hydration improved significantly. Not all treatments received the same amount of discussion time as the prompts were not specific to treatments—thus, dyads may have focused discussions on treatments that generated greater emotional distress and uncertainty. Although research shows the lack of benefit for fluid and nutrition for patients close to death, withdrawing this care may be misconstrued as depriving patients of their basic needs and may have elicited a greater emotional response.35 Moreover, dyads may be more aware of benefits and risks of treatments such as cardiopulmonary resuscition and chose to focus their time on treatments that were more ambiguous.
Decisional quality conflict
Participation in Deciding Together was helpful in reducing decisional conflict in different aspects for patients and caregivers. Patients reported reduced decisional uncertainty (i.e., being clear, feeling sure, and deciding with ease). Caregivers reported improved perceptions of effective decision making (i.e., making an informed choice, perceiving that their decision reflected what was important, expecting to stick with their decision, and being satisfied with their decision).
The intervention may have offered patients an opportunity to clarify their preferences, and for caregivers to support patients during the decision-making process. These findings are supported by the DCM and other dyadic coping studies, which acknowledges individual adjustment in dyadic coping.21,9,36,37 Future studies should explore possible mechanisms of Deciding Together using other methodologies such as naturalistic observation, or examining collaborative ACP in a control group to further understand how dyads' collaborating styles contribute to dyadic ACP decisions.
Readiness for ACP
While there was increase in concordance for R-ACP, these findings were nonsignificant. Secondary data analysis suggested that patients' posttest R-ACP could be influenced by previous completion of ACP. Stronger intervention effects may be observed among dyads who are new to ACP and follow-up studies are recommended.
Limitations
This study was limited by the small sample and lack of diversity among participants, making results less generalizable to other populations. Furthermore, a possibility of selection bias exists due to the low response rate and high rate of previous ACP. Patients who engaged in ACP are more likely to communicate about end-of-life wishes38; thus, it is possible that participants may have been more open to talking about ACP than those who declined participation. In addition, while information on what type of ACP was collected, this was based on patients' self-report/recall, which may have inflated ACP reporting. Nevertheless, the positive findings in this sample suggest that the intervention may be helpful for dyads who have already engaged in ACP, supporting that ACP is a process and preferences can evolve.
Future studies should also include a randomized control group design to support causal inferences. A larger sample would allow for adjustment for confounding variables such as age, health status, relationship factors, and length of intervention delivery. In addition, a follow-up study with health care proxies or caregivers most likely to be designated proxies could confer greater benefit. While the intervention was conducted by the first author solely, which could have introduced bias, processes to improve intervention fidelity were implemented. However, the use of the DCM to guide the intervention and study design is a strength of this study, in an area of research where few theoretical-based interventions for collaborative ACP have been developed.39
Conclusion
Deciding Together is one of the few collaborative ACP interventions focused on the patient–caregiver dyad.40 This study supports the applicability of the DCM for collaborative ACP decision making between older adult HH patients and caregivers, a highly understudied population for which ACP is relevant. This study also provides a foundation for future larger studies, intervention refinement, and expansion.
Deciding Together focuses on building collaboration and positive communication skills during decisions. Patient–caregiver interventions have been developed that focus on joint completion of advance directives.17 However, the assumption that advance directives have been completed sometimes poses a barrier to deeper conversations about treatment preferences.41 As preferences for end-of-life care are likely to change over time for a fifth of patients,42 enhancing dyadic coping may help patients and caregivers navigate the process of decision making more effectively, enhance resilience among dyads facing difficult medical decisions, and improve relational quality throughout the process of ACP. A collaborative approach may help patients and caregivers navigate future decisions more constructively to achieve shared aims, and promote effective coping to potential decisional stressors.
Supplementary Material
Acknowledgments
We thank Dr. Andrew Wilson for providing advice and feedback on the statistical analyses in this study.
Funding Information
The first author was funded by a University of Utah Graduate Research Fellowship during the course of the study.
Author Disclosure Statement
No competing financial interests exist.
Supplementary Material
References
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