이 페이지는 자동 번역되었으며 번역의 정확성을 보장하지 않습니다. 참조하십시오 영문판 원본 텍스트의 경우.

A Mechanism Randomised Controlled Trial of a Three-Agent LLM-Augmented mHealth Intervention for Late-Life Loneliness in Older Adults

2026년 9월 10일 업데이트: The University of Hong Kong
This study examines how a smartphone conversational application affects feelings of loneliness in Cantonese-speaking older adults living in Hong Kong. Seventy-two adults aged 60 or above who report at least moderate loneliness will be randomly assigned to one of two versions of the same application. Both versions look and work the same way, offer the same three conversational companions, and provide the same set of in-app tools. The two versions differ only in how the companions' replies are produced: in one version replies are generated by a large language model, and in the other they are assembled from pre-written templates selected by keyword and conversation state. Participants use the application for four weeks and are then followed for a further four weeks with continued access. The main question is whether any difference between the two versions in emotional loneliness operates through how understood, validated and cared for participants feel during individual conversations. Participants are not told which version they are using, and the researcher who carries out the assessments is also unaware of the assignment.

연구 개요

상세 설명

Loneliness in later life is associated with adverse physical and mental health outcomes. Conversational applications based on large language models have been proposed as a scalable form of support, but most published evaluations remain at the pilot feasibility stage, and few have used a comparator that holds interface richness, attention, and novelty constant. Without such a comparator, any observed benefit cannot be attributed to the language model rather than to the surrounding experience.

This trial addresses that gap using an architecturally matched comparator. Both arms deliver the identical mobile application: the same visual interface, navigation, three named conversational companions, tool layer, and in-app assessment prompts. The sole difference is the backend that generates companion response content. In the Hybrid arm, responses are generated by a large language model using each companion's system prompt, conversation history, and user input, and the arm exhibits language-model-distinctive conversational behaviours including anchoring on specific content, cross-session memory, explicit admission of unfamiliarity, mixed-content routing, and generative summarisation. In the Rule-based arm, responses are produced by a template system driven by keyword matching and conversational state, without cross-session memory and without those behaviours; conversational content in this arm is not transmitted to any external service.

Seventy-two community-dwelling Cantonese-speaking adults aged 60 or above who score at least 2 on the De Jong Gierveld Emotional and Social Loneliness Scale are allocated 1:1, stratified by baseline emotional loneliness using permuted blocks within stratum, with allocation concealment. A designated staff member performs randomisation and onboarding and does not collect outcome data. The Principal Investigator conducts all in-person assessments while unaware of allocation. Participants are not informed which version they use and are debriefed at study completion.

The intervention period is four weeks, followed by four weeks of follow-up with continued application access and continuous usage logging. The primary analysis is a longitudinal 1-1-1 multilevel mediation model with arm as the between-person predictor, session-level perceived responsiveness as the within-person mediator, and emotional loneliness as the outcome; the indirect effect is tested using Monte Carlo confidence intervals. The study is powered for the indirect effect rather than for confirmatory testing of the between-arm main effect, which is reported as an effect estimate with a 95% confidence interval. A falsifiable specification of the proposed mechanism is that an arm advantage appears on emotional loneliness but not on social loneliness.

A three-layer safety architecture operates in both arms: a Cantonese-calibrated distress detector that surfaces Hong Kong crisis resources in real time and alerts the research team; a daily 100% audit of Thought Exercise events against pre-specified scope criteria; and weekly Principal Investigator review of all flags and audits. Pre-specified pause criteria are an intervention-related serious adverse event, boundary-crossed events exceeding 10%, or distress detector recall below 0.90 on a real Cantonese corpus.

연구 유형

중재적

등록 (추정된)

72

단계

  • 해당 없음

연락처 및 위치

이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.

연구 연락처

참여기준

연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.

자격 기준

공부할 수 있는 나이

  • 성인
  • 고령자

건강한 자원 봉사자를 받아들입니다

예

설명

Inclusion Criteria:

  • Aged 60 years or above
  • Self-identified Cantonese as primary language of communication
  • Community-dwelling in Hong Kong (not in residential care)
  • De Jong Gierveld Emotional and Social Loneliness Scale total score of 2 or above at screening, indicating at least moderate loneliness
  • Owns a smartphone, or willing to use a study-provided device
  • Able to demonstrate understanding of the study using the teach-back method
  • Willing to provide written informed consent

Exclusion Criteria:

  • Acute suicidality, defined as a PHQ-9 item 9 score above 1 with reported active intent
  • Currently receiving formal psychiatric treatment
  • Severe hearing or visual impairment precluding application use even with accommodation
  • Self-reported diagnosis of dementia or significant cognitive impairment
  • Unable to demonstrate understanding of the study using the teach-back method
  • Prior participation in the feasibility phase of this research programme

공부 계획

이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.

연구는 어떻게 설계됩니까?

디자인 세부사항

  • 주 목적: 기초 과학
  • 할당: 무작위
  • 중재 모델: 병렬 할당
  • 마스킹: 더블

무기와 개입

참가자 그룹 / 팔
개입 / 치료
실험적: Hybrid arm (LLM-driven)
Participants receive the mobile application with companion responses generated by a large language model backend, using each companion's system prompt, conversation history, and user input. Language-model-distinctive conversational behaviours (content anchoring, cross-session memory, admission of unfamiliarity, mixed-content routing, generative summarisation) are operationally present. Recommended use is at least three sessions per week over four weeks; actual use is at the participant's discretion and is logged.
Mobile application providing three named Cantonese-language conversational companions plus four in-app tools (Action Loop, Thought Exercise, Education, Progress). Companion replies are generated turn-by-turn by a large language model (DeepSeek-V3, accessed via Firebase Cloud Functions), conditioned on the companion's system prompt, retrieved conversation history, and current user input. This arm can therefore produce five conversational behaviours the comparator cannot: anchoring on specific content the participant has just said, memory carried across separate sessions, explicit admission of unfamiliarity, routing of single messages containing mixed emotional and informational content, and generative summarisation. Occurrences are tagged in system logs and analysed as a cumulative within-arm exposure variable. Conversational text is transmitted to the model provider for response generation; participants are advised at consent not to include identifying information. Recommended use is a
활성 비교기: Rule-based arm (template-driven)
Participants receive an application identical in interface, navigation, companion personae, tool layer, and in-app assessment prompts, with companion responses produced by a template system driven by keyword matching and conversational state. Cross-session memory and the language-model-distinctive behaviours are absent. Conversational content is not transmitted externally. Recommended use and logging are identical to the Hybrid arm.
Mobile application identical to the experimental arm in interface, navigation, companion names and personae, tool layer (Action Loop, Thought Exercise, Education, Progress), notification schedule, and all in-app assessment prompts. The sole difference is the response-generation backend: companion replies are assembled from pre-written templates selected by keyword matching and conversational state, with no language model involved. The system retains no memory across sessions, cannot anchor on unanticipated content, cannot admit unfamiliarity outside scripted cases, and cannot generate novel summaries. Conversational content is not transmitted to any external service. This is an attention- and interface-matched active comparator rather than a waitlist or usual-care control: participants receive equivalent contact time, interface richness, tool access, and prompting schedule. Recommended use, expected daily duration, and logging are identical to the experimental arm.

연구는 무엇을 측정합니까?

주요 결과 측정

결과 측정
측정값 설명
기간
Session-level perceived responsiveness (primary mediator)
기간: After each conversation session, Weeks 1 through 4
Brief perceived-responsiveness measure administered in-app immediately after each companion conversation. Single-item sliders scored 1-7 covering Understanding, Validation, Caring and Insensitivity. Higher scores indicate greater perceived responsiveness. This is the within-person mediator in the pre-specified primary mediation model, not an efficacy endpoint.
After each conversation session, Weeks 1 through 4
Change in emotional loneliness (De Jong Gierveld emotional subscale)
기간: Baseline (Week 0) and Week 4
De Jong Gierveld Emotional and Social Loneliness Scale, 3-item emotional subscale. Score range 0-3; higher scores indicate greater emotional loneliness. Change from baseline to Week 4. This is the outcome variable in the pre-specified primary mediation model. The trial is powered for the indirect effect via session-level perceived responsiveness and is not powered for confirmatory testing of the between-arm difference, which is reported as an effect estimate with a 95% confidence interval.
Baseline (Week 0) and Week 4

공동 작업자 및 조사자

여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.

연구 기록 날짜

이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.

연구 주요 날짜

연구 시작 (추정된)

2026년 9월 21일

기본 완료 (추정된)

2026년 12월 31일

연구 완료 (추정된)

2026년 12월 31일

연구 등록 날짜

최초 제출

2026년 9월 10일

QC 기준을 충족하는 최초 제출

2026년 9월 10일

처음 게시됨 (실제)

2026년 9월 16일

연구 기록 업데이트

마지막 업데이트 게시됨 (실제)

2026년 9월 16일

QC 기준을 충족하는 마지막 업데이트 제출

2026년 9월 10일

마지막으로 확인됨

2026년 9월 1일

추가 정보

이 연구와 관련된 용어

약물 및 장치 정보, 연구 문서

미국 FDA 규제 의약품 연구

아니

미국 FDA 규제 기기 제품 연구

아니

이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .

구독하다