Measuring patients' medical treatment preferences in advance care planning: development and validation of the Treat-Me-ACP instrument - a secondary analysis of a cluster-randomized controlled trial.

BACKGROUND: Advance Care Planning interventions should be evaluated as broadly as possible to gain a holistic understanding of the Advance Care Planning process. However, validated early stage outcome instruments are lacking. Therefore, the Treatment-Preference-Measure-Advance Care Planning (Treat-Me-ACP) instrument was developed and validated as part of the cluster-randomized controlled trial STADPLAN (Study on Advance Care Planning in care-dependent community-dwelling older persons) to assess the effects of Advance Care Planning interventions on patients' medical treatment preferences. METHODS: The design of Treat-Me-ACP is based on the Emanuel Medical Directive and the Life Support Preferences Questionnaires. Using a multi-stage team approach a preliminary version of the Treat-Me-ACP was developed and pre-tested. The pre-tested instrument consists of one global medical care goal-item, five hypothetical scenarios with five hypothetical treatments, and one how would you feel-item within each scenario. A total of five scenario preference scores and five treatment preference scores can be formed. This version was subsequently applied to a subsample of the STADPLAN project (n = 80) to assess patient's preferences at baseline (T0) and at 12-month follow-up (T2). The further validation steps were based on this subsample and included: (1) acceptance by using completion rate and frequencies of missing data, (2) internal consistency by using Cronbach's α to test whether it was possible to create preference scores by scenario and treatment, (3) concurrent validation examining the association between the global medical care goal-item and the preference scores and the association between the how would you feel-items and the scenario preference scores, and (4) responsiveness of the instrument to changes in preferences for life-sustaining treatments by comparing preference scores from T0 to T2 between study groups. RESULTS: Acceptance of the instrument was high. Results of concurrent validation indicate that the five scenarios represent the global medical care goal well. The preference scores showed an average tendency for decreasing preferences for life-sustaining treatments across all scales for the intervention group during study follow-up. CONCLUSIONS: The Treat-Me-ACP can be used to evaluate the dynamics of patients' medical treatment preferences in Advance Care Planning. It has been validated for care-dependent community-dwelling older persons and can be used as an additional outcome measure in evaluating the effectiveness of ACP interventions. TRIAL REGISTRATION: German Clinical Trials Register: DRKS00016886 on 04/06/2019.

Factors Influencing the Acceptability, Acceptance, and Adoption of Conversational Agents in Health Care: Integrative Review.

BACKGROUND: Conversational agents (CAs), also known as chatbots, are digital dialog systems that enable people to have a text-based, speech-based, or nonverbal conversation with a computer or another machine based on natural language via an interface. The use of CAs offers new opportunities and various benefits for health care. However, they are not yet ubiquitous in daily practice. Nevertheless, research regarding the implementation of CAs in health care has grown tremendously in recent years. OBJECTIVE: This review aims to present a synthesis of the factors that facilitate or hinder the implementation of CAs from the perspectives of patients and health care professionals. Specifically, it focuses on the early implementation outcomes of acceptability, acceptance, and adoption as cornerstones of later implementation success. METHODS: We performed an integrative review. To identify relevant literature, a broad literature search was conducted in June 2021 with no date limits and using all fields in PubMed, Cochrane Library, Web of Science, LIVIVO, and PsycINFO. To keep the review current, another search was conducted in March 2022. To identify as many eligible primary sources as possible, we used a snowballing approach by searching reference lists and conducted a hand search. Factors influencing the acceptability, acceptance, and adoption of CAs in health care were coded through parallel deductive and inductive approaches, which were informed by current technology acceptance and adoption models. Finally, the factors were synthesized in a thematic map. RESULTS: Overall, 76 studies were included in this review. We identified influencing factors related to 4 core Unified Theory of Acceptance and Use of Technology (UTAUT) and Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) factors (performance expectancy, effort expectancy, facilitating conditions, and hedonic motivation), with most studies underlining the relevance of performance and effort expectancy. To meet the particularities of the health care context, we redefined the UTAUT2 factors social influence, habit, and price value. We identified 6 other influencing factors: perceived risk, trust, anthropomorphism, health issue, working alliance, and user characteristics. Overall, we identified 10 factors influencing acceptability, acceptance, and adoption among health care professionals (performance expectancy, effort expectancy, facilitating conditions, social influence, price value, perceived risk, trust, anthropomorphism, working alliance, and user characteristics) and 13 factors influencing acceptability, acceptance, and adoption among patients (additionally hedonic motivation, habit, and health issue). CONCLUSIONS: This review shows manifold factors influencing the acceptability, acceptance, and adoption of CAs in health care. Knowledge of these factors is fundamental for implementation planning. Therefore, the findings of this review can serve as a basis for future studies to develop appropriate implementation strategies. Furthermore, this review provides an empirical test of current technology acceptance and adoption models and identifies areas where additional research is necessary. TRIAL REGISTRATION: PROSPERO CRD42022343690; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=343690.

Contextual factors influencing advance care planning in home care: process evaluation of the cluster-randomised controlled trial STADPLAN.

BACKGROUND: The STADPLAN study is a cluster-randomised controlled trial including 27 home care services in Germany. It assesses the effect of an advance care planning (ACP) intervention delivered by trained nurses to older care-dependent patients. Patients received two ACP conversations and an information brochure. Nurses were educated through a two-day programme and topic guides structuring the conversations. Objectives of the process evaluation were to determine: [1] whether the intervention was implemented as planned, [2] which change mechanisms were observed, [3] whether targeted process outcomes were achieved and [4] in which way contextual factors influenced the implementation process. METHODS: The process evaluation is based on a mixed methods approach following the recommendations of the UK-MRC framework for the development and evaluation of complex interventions. Qualitative and quantitative assessments were developed and analysed guided by a logic model comprising intervention, participants, mechanisms of change and context factors. The results of the main trial will be published elsewhere. RESULTS: Educational programme and topic guides were mostly implemented as planned and resulted in motivation, knowledge, and perceived competencies to facilitate ACP conversations in nurses. Deviances in the performance of ACP conversations indicated patients' varied individual needs, but also obstacles like reluctance of patients and caregivers to participate actively and time constraints of nurse facilitators. Patients and caregivers reported increased awareness of ACP, planning and other activities indicating that targeted process outcomes could be achieved. The relevance of multifaceted contextual factors acting as barriers or facilitators for the engagement in ACP interventions on the individual, organisational and macro level was evident. CONCLUSIONS: The process evaluation elicits obstacles and achievements of the ACP intervention. The logic model organised a plethora of mixed methods data into a holistic picture of multifaceted results. Nurses as ACP facilitators in home care can fulfil a crucial initiating role based on a trusting relationship with their patients. To support older care-dependent people's ACP engagement, access should be simplified. Furthermore, education for nurse facilitators and sufficient resources for service provision are needed. Independent of monetary reimbursement, healthcare providers must respect patients' choice for or against any ACP intervention. ETHICS AND TRIAL REGISTRATION: Approved by the Ethics Committees of Martin Luther University Halle-Wittenberg (Ref.-No. 2019-045), Carl von Ossietzky University Oldenburg (Ref.-No. 2019-024), and University of Lübeck (Ref.-No. 19-080). GERMAN CLINICAL TRIALS REGISTER: DRKS00016886. Registered retrospectively 04/06/2019, first participant included 29/05/2019.