Platform used and method of administration: The technology is packaged in a software app that can be used across a range of mobile smart devices. The current Android version of the app tested during this study was installed on a Samsung Note 3 (SM-N9005) device. The ePAT is also an observational (informant-based) tool, which can be administered by a care worker or clinician (user) using a smart device. The user must be trained on the use of the tool and be familiar with the patient undergoing assessment. The user needs to navigate from one domain to another to complete the assessment.
Scoring: The ePAT uses a hybrid model in which the Face domain is fully automated while other domains (Domains 2–6) are questionnaire-based checklists manually completed by the assessor, using the mobile device. Similar to the Pain Assessment Checklist for Seniors with Limited Ability to Communicate (PACSLAC), a binary (2-point) format is adopted to evaluate the presence (score = 1) or absence (score = 0) of pain related behaviors on each of the 42 items. Magnitude of pain is measured by obtaining a cumulative score across all items. Total pain score, cumulated over all domains, can range from 0–42, with the corresponding band categories of pain intensity (no pain, mild, moderate, severe) to be explored in this study.
Conceptual foundation: The tool was developed on the basis of the definition of pain as “an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage” . There is also a great need for developing novel and innovative pain assessment instruments for non-verbal people with dementia as evident in the current literature. A meta-review by Lichtner et al. suggested that new painassessment tools need to be developed on an innovative conceptual basis . In addition, a review by Hadjistavropoulos et al. has strongly recommended that including a FACS-based pain expression should be considered by researchers for future development and refinement of pain instruments for older adults with dementia .
Therefore, we considered these main principles in designing the ePAT:
(a) Through integration of FACS into the tool
(b) Via automation: this is achieved by using a deep learning algorithm, with the purpose of reducing proxy rating error associated with human judgement
(c) Use of a binary (yes/no) approach to the identification of the presence of non-facial pain cues
(a) Inclusion of AGS items in the tool to identify subtle behavioral changes based on pain items specifically geared towards older persons with dementia
3) Portability and smart device interoperability
(a) Smart device capabilities (such as high computational efficiency, e.g., processing power, digitization, and in-built cameras) and their popular use (due to reasonable costs, use with various platforms, e.g., Android, iOS) make them suitable to facilitate pain assessment at the point-of-care.
A comparative account between the ePAT and APS is summarized in Table 1.
All clinical assessments were performed in accordance with principles outlined in the Declaration of Helsinki, Alzheimer’s Australia Guidelines, and clauses for undertaking research in cognitively impaired individuals by the Australian National Statement for Ethical Conduct in Human Research.
Ethical approval (HREC: HR10/2014) was granted by Human Research Ethics Committee, Curtin University, Western Australia and by ethics review boards of participating facilities. Informed consent could not be elicited from residents with dementia due to their impaired cognitive capacity. Thus, proxy consents were provided by relatives or an authorized representative of the cognitively impaired residents prior to participation. Proxies were notified that they could revoke their consent at any time without affecting the quality of care or the relationship of participants with those working in the aged care facility. Verbal explanations using very simple language (e.g., “we are checking whether you have any pain today by taking a short video of you”) were also used to explain the study to theresidents.
Design and setting
The study was a prospective observational study which involved residents from three metropolitan aged care homes (ACH) in Perth, Western Australia.
Residents were eligible to enroll if they met the following criteria: (1) age greater than 60 y, (2) living in a designated dementia unit of the ACH, (3) had a diagnosis of dementia, (4) their cognitive score based on the Mini-Mental State Examination (MMSE): <19 or Psychogeriatric Assessment Scale–Cognitive Impairment Scale (PAS-CIS): >10, and (5) possessed a documented history of a chronic pain condition such as osteoarthritis or currently suffer from acute (e.g., urinary tract infection), recurrent (e.g., gout) or incidental pain (e.g., pressure sores).
Residents were excluded from the study if they could not partially or completely exhibit any facial expression (for example as a result of a facial palsy), were clinically too unwell, or where it was inappropriate for them to be assessed for pain, as determined by the treating doctor.
The study was conducted over a 13-week period in each of the three participating ACHs. The study was initiated at Aged Care Home 1 (ACH 1) from March-July 2015, then Aged Care Home 2 (ACH 2) from October 2015-January 2016, and Aged Care Home 3 (ACH 3) from January-April 2016. The choice of 13 weeks was made to allow adequate time for testing to occur under various conditions and while residents were doing their routine activities (i.e., at rest and upon movements, e.g., walking, repositioning, bathing, etc.).
Each resident was independently evaluated using the two assessment tools during routine care. The APS (i.e., standard care) was administered by a staff member (nurse or carer) employed by the facility as part of normal care, while the ePAT (the new tool) was administered, in most instances, by the primary researcher (MA), although health care professionals (e.g., registered nurse), personal care workers, or nursing and occupational therapy students also conducted some assessments. All raters were blinded to each other’s assessments. With the exception of the health science students, those involved in performing the assessments were already experienced in using APS or ePAT. Practical training on the use of the ePAT and the APS was delivered by the primary investigator to health science students. Paired pain assessments were undertaken during various levels of activities such as walking, after toileting or showering to induce nociceptive painful experiences, and during resting to mimic non-nociceptive periods.
Pain ratings were conducted mainly during daytime between 8 am and 6 pm. Ratings were undertaken indoors in multiple locations (e.g., activity room, resident’s room, dining room) inside the ACHs. In cases where the ePAT assessor was unfamiliar with the resident, care staff not involved with the study were consulted to answer various questions about residents’ behaviors (e.g., sleeping/eating pattern). Both ePAT and APS assessments were brief in nature and they were administered either concurrently or within 2-3 min of each other. The order in which the assessments were delivered was random to minimize the possibility of any learningeffect.
Standard descriptive statistics were used to summarize the study participants and number of assessments conducted (frequencies and percentages for categorical variables, means, standard deviations, and ranges for continuous variables).
Concurrent validity was assessed using the Pearson’s correlation coefficient between the overall pain scores assigned by the APS and ePAT instruments, and separately for observations made at rest and following movement. The correlation is not a measure of exact agreement, as the instruments are based on different scoring mechanisms, but a strong correlation would indicate that the ePAT is equivalent to the APS up to a scaling factor. A refinement of the Pearson’s correlation coefficient was also calculated, following the method of Lam et al. , using a SAS macro described by Hamlett . This refinement took into account the repeated measurements made on each participant in case agreement between APS and ePAT differed between participants.
Discriminant validity investigated whether the agreement between APS and ePAT depended on the conditions (at rest or with movement). This was explored by using the difference in pain scores (APS minus ePAT) as the dependent variable in a random effects regression model, with the timing (rest or with movement) as the independent variable and the subject number as the random effect. Naming the subject as a random effect in this model took into account any correlations between the repeated measures made on each study participant. The p-value associated with timing indicated its influence on the agreement between measures.
Inter-rater reliability was assessed by classifying the pain scores for APS and ePAT into four categories from no pain to mild, moderate, and severe pain. Agreement between the measures according to these categories was then assessed using the Cohen’s kappa statistic. The standard (unweighted) kappa is a measure of exact agreement within categories, while the weighted kappa gives some weight to small disagreements.
Internal consistency between the two measures was calculated using Cronbach’s alpha. This assesses the extent to which two or more measures are essentially measuring the same construct . It was used in this study to compare the overall APS and ePAT scores. Values of Cronbach’s alpha above 0.7 are indicative of a good agreement between measures .
Statistical analyses were performed using the SAS version 9.2 software (SAS Institute Inc, Cary, NC, USA, 2008).
A total of 40 residents were recruited into the study from the three aged care homes. The average age of the participants was 79.7 y (SD: 9.1; range: 60 to 98 y). The majority of residents were females (70%) and Caucasians (n = 39), with the remaining participant being Asian. The residents had a range of chronic pain conditions as a result of arthritis (e.g., osteoarthritis, rheumatoid arthritis and gout), previous injuries and/or surgeries, skin tears and sores, dental disorders (e.g., sore gums associated with gingivitis), and neuropathic pain (e.g., post-herpetic neuralgia). Seventy percent of the cohort had one or more documented chronic pain diagnoses. A number of participating residents were bed-ridden, immobile or had limited mobility. All residents were identified as having moderate to severe cognitive impairment based on a PAS-CIS score in the range of 10–15 and 16–21, respectively. Eighty-seven percent of residents had severe impairment. MMSE scores were unable to be completed for most residents due to severe impairments and were only recorded for eight residents with a mean of 14.0±3.9. More than half (57.5%) of the sample had a diagnosis of Alzheimer’s dementia while 25% reported to have an unspecified type of dementia. Other documented dementias were frontotemporal dementia (7.5%), Lewy body dementia (2.5%), Parkinsonian’s dementia (5%), and mixed dementia (2.5%). Refer to Table 2 for further details.