Feasibility study protocol of the PainChek app to assess the efficacy of a social robot intervention for people with dementia

Associations between facial expressions and observational pain in residents with dementia and chronic pain

AIM

To identify specific facial expressions associated with pain behaviors using the PainChek application in residents with dementia.

DESIGN

This is a secondary analysis from a study exploring the feasibility of PainChek to evaluate the effectiveness of a social robot (PARO) intervention on pain for residents with dementia from June to November 2021.

METHODS

Participants experienced PARO individually five days per week for 15 min (once or twice) per day for three consecutive weeks. The PainChek app assessed each resident's pain levels before and after each session. The association between nine facial expressions and the adjusted PainChek scores was analyzed using a linear mixed model.

RESULTS

A total of 1820 assessments were completed with 46 residents. Six facial expressions were significantly associated with a higher adjusted PainChek score. Horizontal mouth stretch showed the strongest association with the score, followed by brow lowering parting lips, wrinkling of the nose, raising of the upper lip and closing eyes. However, the presence of cheek raising, tightening of eyelids and pulling at the corner lip were not significantly associated with the score. Limitations of using the PainChek app were identified.

CONCLUSION

Six specific facial expressions were associated with observational pain scores in residents with dementia. Results indicate that automated real-time facial analysis is a promising approach to assessing pain in people with dementia. However, it requires further validation by human observers before it can be used for decision-making in clinical practice.

IMPACT

Pain is common in people with dementia, while assessing pain is challenging in this group. This study generated new evidence of facial expressions of pain in residents with dementia. Results will inform the development of valid artificial intelligence-based algorithms that will support healthcare professionals in identifying pain in people with dementia in clinical situations.

REPORTING METHOD

The study adheres to the CONSORT reporting guidelines.

PATIENT OR PUBLIC CONTRIBUTION

One resident with dementia and two family members of people with dementia were consulted and involved in the study design, where they provided advice on the protocol, information sheets and consent forms, and offered valuable insights to ensure research quality and relevance.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trials Registry number (ACTRN12621000837820).

Using AI-Based Technologies to Help Nurses Detect Behavioral Disorders: Narrative Literature Review

BACKGROUND

The behavioral and psychological symptoms of dementia (BPSD) are common among people with dementia and have multiple negative consequences. Artificial intelligence-based technologies (AITs) have the potential to help nurses in the early prodromal detection of BPSD. Despite significant recent interest in the topic and the increasing number of available appropriate devices, little information is available on using AITs to help nurses striving to detect BPSD early.

OBJECTIVE

The aim of this study is to identify the number and characteristics of existing publications on introducing AITs to support nursing interventions to detect and manage BPSD early.

METHODS

A literature review of publications in the PubMed database referring to AITs and dementia was conducted in September 2023. A detailed analysis sought to identify the characteristics of these publications. The results were reported using a narrative approach.

RESULTS

A total of 25 publications from 14 countries were identified, with most describing prospective observational studies. We identified three categories of publications on using AITs and they are (1) predicting behaviors and the stages and progression of dementia, (2) screening and assessing clinical symptoms, and (3) managing dementia and BPSD. Most of the publications referred to managing dementia and BPSD.

CONCLUSIONS

Despite growing interest, most AITs currently in use are designed to support psychosocial approaches to treating and caring for existing clinical signs of BPSD. AITs thus remain undertested and underused for the early and real-time detection of BPSD. They could, nevertheless, provide nurses with accurate, reliable systems for assessing, monitoring, planning, and supporting safe therapeutic interventions.

Development and validation of a point-of-care nursing mobile tool to guide the diagnosis of malnutrition in hospitalized adult patients: a multicenter, prospective cohort study

Malnutrition is a prevalent and severe issue in hospitalized patients with chronic diseases. However, malnutrition screening is often overlooked or inaccurate due to lack of awareness and experience among health care providers. This study aimed to develop and validate a novel digital smartphone-based self-administered tool that uses facial features, especially the ocular area, as indicators of malnutrition in inpatient patients with chronic diseases. Facial photographs and malnutrition screening scales were collected from 619 patients in four different hospitals. A machine learning model based on back propagation neural network was trained, validated, and tested using these data. The model showed a significant correlation (p < 0.05) and a high accuracy (area under the curve 0.834-0.927) in different patient groups. The point-of-care mobile tool can be used to screen malnutrition with good accuracy and accessibility, showing its potential for screening malnutrition in patients with chronic diseases.

Implementing PainChek and PARO to Support Pain Assessment and Management in Residents with Dementia: A Qualitative Study

BACKGROUND

Pain is a common problem but often undiagnosed and untreated in people with dementia.

AIMS

This study explored the experiences of residents with dementia, family, andformal carers with (1) pain assessment and management for residents with dementia; (2) the use of the PainChek app for pain assessment, and (3) the use of a social robot PARO for pain management in residents with dementia.

DESIGN

A qualitative study.

SETTINGS/PARTICIPANTS

Interviews were conducted with 13 residents withdementia, three family members, and 18 formal carers from a residential aged carefacility.

METHOD

Residents with dementia interacted with PARO for 15 mins, five days perweek for three weeks. The PainChek app assessed pain levels before and after eachsession. After three-week intervention, individual interviews were conducted withresidents, family, and formal carers who experienced or observed the use of PainChekapp and PARO for residents. Interviews were audio-recorded, transcribed, andanalyzed using thematic analysis.

RESULTS

Four themes were identified regarding pain in residents with dementia: (1) the impact, challenges and strategies of pain assessment and management; (2) benefits and barriers of using PainChek app to assess pain; (3) benefits of interacting with PARO to manage pain and behavioral symptoms; and (4) implementing PainChek app and PARO to support pain assessment and management in dementia care.

CONCLUSIONS

Technology, such as PainChek and PARO, is promising to improve painassessment and reduce pain for people with dementia. Barriers to using technologyinclude limited staff training and the implementation of person-centered care.

Socially assistive robots for people with dementia: Systematic review and meta-analysis of feasibility, acceptability and the effect on cognition, neuropsychiatric symptoms and quality of life

BACKGROUND

There is increasing interest in using robots to support dementia care but little consensus on the evidence for their use. The aim of the study is to review evidence about feasibility, acceptability and clinical effectiveness of socially assistive robots used for people with dementia.

METHOD

We conducted a systematic review and meta-analysis. We searched MEDLINE, EMBASE, PsychINFO, CINHAL, IEEE Xplore Digital Library, and EI Engineering Village from inception to 04 - 02-2022 - included primary studies assessing feasibility, acceptability, or effectiveness of socially assistive robots for people with dementia. Two independent reviewers screened studies for eligibility, and assessed quality. Narrative synthesis prioritized higher quality studies, and random-effect meta-analyses compared robots with usual care (UC) or active control (AC) immediately after the intervention (short-term; ST) or long-term (LT) on cognition, neuropsychiatric symptoms, and quality of life.

FINDINGS

66 studies and four categories of robots were eligible: Companion robots (Pet and humanoid companion robots), telepresence communication robots, homecare assistive robots and multifunctional robots. PARO (companion robot seal) was feasible and acceptable but limited by its weight, cost, and sound. On meta-analysis, PARO had no ST or LT compared to UC or AC over 5-12 weeks on agitation (ST vs UC, 4 trials, 153 participants: pooled standardized mean difference (SMD) 0.25; - 0.57 to 0.06; LT vs UC; 2 trials, 77 participants, SMD = -0.24; - 0.94, 0.46), cognition (ST vs UC, 3 trials, 128 participants: SMD= 0.03; -0.32, 0.38), overall neuropsychiatric symptoms (ST vs UC, 3 trials, 169 participants: SMD= -0.01; -0.32, 0.29; ST vs AC, 2 trials, 145 participants: SMD =0.02, -0.71, 0.85), apathy (ST vs AC, 2 trials, 81 participants: SMD= 0.14; 0.29, 0.58), depression (ST vs UC, 4 trials, 181 participants; SMD= 0.08; -0.52, 0.69; LT vs UC: 2 trials, 77 participants: SMD =0.01; -0.75, 0.77), anxiety (ST vs UC: 2 trials, 104 participants, SMD= 0.24; -0.85, 1.33) and quality of life (ST vs UC, 2 trials, 127 participants: SMD=-0.05; -0.52, 0.42; ST vs AC: 2 trials, 159 participants, SMD =-0.36, -0.76, 0.05). Robotic animals, humanoid companion robots, telepresence robots and multifunctional robots were feasible and acceptable. However, humanoid companion robots have speech recognition problems, and telepresence robots and multifunctional robots were often difficult to use. There was mixed evidence about the feasibility of homecare robots. There was little evidence on any of these robots' effectiveness.

CONCLUSION

Although robots were generally feasible and acceptable, there is no clear evidence that people with dementia derive benefit from robots for cognition, neuropsychiatric symptoms, or quality of life. We recommend that future research should use high quality designs to establish evidence of effectiveness.