Framing Effects on End-of-Life Preferences Among Latino Elders

Ortiz, Daniel Vélez; Martinez, Rubén O.; Espino, David V.

doi:10.1080/00981389.2015.1059398

Cited by 5 publications

(9 citation statements)

References 40 publications

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“…We stratified data according to study type (i.e., qualitative, quantitative, mixed methods observation, interventional) using standard extraction templates in Excel and Access datasheets. Data were extracted and assigned to the following categories: Study reference (i.e., first author, year of publication, country of study origin); Study aim; Study setting; Sample size; Population characteristics (e.g., age, sex, definition of multimorbidity, patient prognosis or illness severity, cancer or non-malignant condition); Preference assessment method (e.g., interview or questionnaire); Context of preference (i.e., hypothetical/real, preference-sensitive situation); Information provided by the authors on the presentation of alternatives (e.g., positive or negative framing [16,17]); Description of phenomenon of interest (EoL care elements that patients were asked about, e.g., resuscitation preference); Results of described phenomenon of interest (e.g., proportion of participants expressing a preference for a specific type of EoL care).…”

Section: Data Itemsmentioning

confidence: 99%

“…Studies were categorized according to study design, whereby the assessment depended on the employed methodology. The tool was adapted to include a column evaluating the existence of a framing effect, which is a cognitive bias that occurs when the way information is presented influences the choices patients make [16,17]. The framing effect was independently assessed by two review authors (A.I.G.-G., M.-S.B.…”

Section: Risk Of Biasmentioning

confidence: 99%

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End-of-Life Care Preferences of Older Patients with Multimorbidity: A Mixed Methods Systematic Review

González‐González

Schmucker

Nothacker

et al. 2020

JCM

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Unpredictable disease trajectories make early clarification of end-of-life (EoL) care preferences in older patients with multimorbidity advisable. This mixed methods systematic review synthesizes studies and assesses such preferences. Two independent reviewers screened title/abstracts/full texts in seven databases, extracted data and used the Mixed Methods Appraisal Tool to assess risk of bias (RoB). We synthesized findings from 22 studies (3243 patients) narratively and, where possible, quantitatively. Nineteen studies assessed willingness to receive life-sustaining treatments (LSTs), six, the preferred place of care, and eight, preferences regarding shared decision-making processes. When unspecified, 21% of patients in four studies preferred any LST option. In three studies, fewer patients chose LST when faced with death and deteriorating health, and more when treatment promised life extension. In 13 studies, 67% and 48% of patients respectively were willing to receive cardiopulmonary resuscitation and mechanical ventilation, but willingness decreased with deteriorating health. Further, 52% of patients from three studies wished to die at home. Seven studies showed that unless incapacitated, most patients prefer to decide on their EoL care themselves. High non-response rates meant RoB was high in most studies. Knowledge of EoL care preferences of older patients with multimorbidity increases the chance such care will be provided.

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Section: Data Itemsmentioning

confidence: 99%

Section: Risk Of Biasmentioning

confidence: 99%

End-of-Life Care Preferences of Older Patients with Multimorbidity: A Mixed Methods Systematic Review

González‐González

Schmucker

Nothacker

et al. 2020

JCM

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“…Sixteen studies were conducted in community-based settings [ 18 – 33 ], eight in out-patient clinical care units (i.e., dialysis centres, cancer clinics, HIV clinic) [ 34 – 41 ], seven in urban hospitals [ 42 – 48 ] and six in primary care settings [ 49 – 54 ]. Eleven studies focused on a multi-racial/ethnic population [ 20 , 30 , 37 , 42 , 45 – 49 , 51 , 53 ]; 10 on patients of Latino descent [ 23 , 26 , 27 , 34 , 36 , 39 , 44 , 50 , 52 , 54 ] and African American descent [ 18 , 19 , 21 , 24 , 32 , 35 , 38 , 40 , 41 , 43 ]; two on patients of Chinese American descent [ 22 , 25 ]; and one on patients of Chinese Australian [ 33 ], Korean American [ 28 ], South Asian Indian American [ 29 ] and Asian American descent [ 31 ]. Study characteristics can be found in S1 Table .…”

Section: Resultsmentioning

confidence: 99%

“…[ 21 , 22 , 24 , 26 – 29 , 31 , 32 , 35 , 38 , 40 , 41 , 45 , 46 ]; healthcare provider-led interventions (i.e., palliative care consults, patient navigators, lay health workers, etc.) [ 34 , 37 , 42 – 44 , 47 – 49 ]; educational tools (i.e., videos, booklets) [ 18 – 20 , 25 , 33 , 53 , 54 ]; paper-based and electronic decision aids [ 30 , 50 – 52 ]; and communication strategies [ 23 , 36 , 39 ]. Twenty-seven tools were aimed at supporting patients [ 7 , 21 , 23 – 27 , 29 , 31 – 34 , 36 – 39 , 42 – 48 , 50 – 53 ]; five at supporting family members [ 18 – 20 , 28 , 30 ]; four at supporting both patients and families [ 35 , 40 , 41...…”

Section: Resultsmentioning

confidence: 99%

The effect of end-of-life decision-making tools on patient and family-related outcomes of care among ethnocultural minorities: A systematic review

et al. 2022

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Background End-of-life decision-making tools are used to establish a shared understanding among patients, families and healthcare providers about medical treatment and goals of care. This systematic review aimed to understand the availability and effect of end-of-life decision-making tools on: (i) goals of care and advance care planning; (ii) patient and/or family satisfaction and well-being; and (iii) healthcare utilization among racial/ethnic, cultural, and religious minorities. Methods A search was conducted in four electronic databases (inception to June 2021). Articles were screened for eligibility using pre-specified criteria. We focused on adult patients (aged ≥18 years) and included primary research articles that used quantitative, qualitative, and mixed-methods designs. Complementary quality assessment tools were used to generate quality scores for individual studies. Extracted data were synthesized by outcome measure for each type of tool, and an overall description of findings showed the range of effects. Results Among 14,316 retrieved articles, 37 articles were eligible. We found that advance care planning programs (eleven studies), healthcare provider-led interventions (four studies), and linguistically-tailored decision aids (three studies) increased the proportion of patients documenting advance care plans. Educational tools (three studies) strongly reduced patient preferences for life-prolonging care. Palliative care consultations (three studies) were strongly associated with do-not-resuscitate orders. Advance care planning programs (three studies) significantly influenced the quality of patient-clinician communication and healthcare provider-led interventions (two studies) significantly influenced perceived patient quality of life. Conclusion This review identified several end-of-life decision-making tools with impact on patient and family-related outcomes of care among ethnocultural minorities. Advance care planning programs, healthcare provider-led interventions and decision aids increased documentation of end-of-life care plans and do-not-resuscitate orders, and educational tools reduced preferences for life-prolonging care. Further research is needed to investigate the effect of tools on healthcare utilization, and with specific patient population subgroups across different illness trajectories and healthcare settings.

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“… 14 – 16 More specifically to ACP, BE research has shown that the way questions and information are framed to patients in EOL decision-making can impact their preferences and choices. 17 , 18 Studies have also explored other cognitive barriers to ACP uptake, and the potential for the use of behavioural theories in EOL care decision-making. 19 , 20 In fact, simply being aware of potential behavioural biases can assist patient’s ability to revise counterproductive beliefs in the ACP decision process.…”

Section: Introductionmentioning

confidence: 99%

Cognitive and behavioural bias in advance care planning

et al. 2022

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Background: We explore cognitive and behavioural biases that influence individual’s willingness to engage advance care planning (ACP). Because contexts for the initiation of ACP discussions can be so different, our objective in this study was to identify specific groups, particular preferences or uniform behaviours, that may be prone to cognitive bias in the ACP decision process. Method: We collected data from the Australian general public ( n = 1253), as well as general practitioners (GPs) and nurses ( n = 117) including demographics, stated preference for ACP decision-making; six cognitive bias tests commonly used in Behavioural Economics; and a framing experiment in the context of ACP. Results: Compared to GPs ( M = 57.6 years, SD = 17.2) and the general public (58.1 years, SD = 14.56), nurses on average recommend ACP discussions with patients occur approximately 15 years earlier ( M = 42.9 years, SD = 23.1; p < 0.0001 in both cases). There is a positive correlation between the age of the general population and the preferred age for the initial ACP discussion ( ρ = 0.368, p < 0.001). Our shared decision-making analysis shows the mean share of doctor’s ACP input is viewed to be approximately 40% by the general public, significantly higher than health professionals (GPs and nurses), who believe doctors should only contribute approximately 20% input. The general public show varying relationships (all p < 0.05) for both first ACP discussion, and shared decision-making for five of six cognitive tests. However, for health professionals, only those who exhibit confirmation bias show differences (8.4% higher; p = 0.035) of patient’s input. Our framing experiment results show that positive versus negative framing can result in as much as 4.9–7.0% shift in preference for factors most relevant to ACP uptake. Conclusion: Understanding how GPs, nurses and patients perceive, engage and choose to communicate ACP and how specific groups, particular preferences or uniform behaviours, may be prone to cognitive bias in the decision process is of critical importance for increasing future uptake and efficient future healthcare provision.

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Framing Effects on End-of-Life Preferences Among Latino Elders

Cited by 5 publications

References 40 publications

End-of-Life Care Preferences of Older Patients with Multimorbidity: A Mixed Methods Systematic Review

End-of-Life Care Preferences of Older Patients with Multimorbidity: A Mixed Methods Systematic Review

The effect of end-of-life decision-making tools on patient and family-related outcomes of care among ethnocultural minorities: A systematic review

Cognitive and behavioural bias in advance care planning

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