Study design
An interviewer-administered survey was used.
Participants
In this study, four residential care homes in Suzhou were selected by convenience sampling and all the senior residents meeting the following inclusion criteria were surveyed: (1) aged ≥65 years; (2) a resident of the RCH for≥3 months; 3) willing to participate in the survey and able to sign the informed consent. Exclusion criteria included: (1) cerebral diseases caused by various underlying medical conditions; (2) acute onset of diseases within the past 3 months, e.g. stroke, heart attack, asthma attack, acute pneumonia, acute bronchitis, etc.; (3) a diagnosis of active epilepsy; (4) a diagnosis of dementia; (5) severe sensory impairments, making them unable to complete cognitive assessment test. The above-mentioned conditions were diagnosed by a doctor.
Instruments
Sociodemographic questionnaire
A sociodemographic questionnaire was used, consisting of key influencing factors for cognitive functioning in older adults extracted from relevant literature, i.e. age, sex, height and weight (converted into body mass index (BMI) by the interviewer on site), level of education (elementary school and below, junior high school, senior high school/secondary school, college and above), monthly income (<5000RMB, 5000-10000RMB, >10000RMB, frequency of socialization (Never, ≤3 times/week, > 3 times/week), type of underlying diseases (categorized into “none” or “cardiovascular/cerebrovascular diseases and/or diabetes” or “others” during statistical analyses.), and use of mobile devices (users, non-users). Mobile devices refer to any handheld computer or smartphone, including smartphones, tablets, e-readers, personal digital assistants (PDAs) and portable music/video players with smart capabilities and Internet access. The participants were asked whether they possessed a mobile device and what they used it for. If they possessed a device and used the smart capabilities and Internet access of the device for communication, entertainment and information search, they were categorized as “users of mobile devices”. If they did not possess a device or they possessed a device but did not use it/did not know how to use it (e.g. they used a smartphone in the same way as a feature phone), they were classified as “non-users”.
Montreal cognitive assessment (MoCA)
Use of the MoCA is recommended by the “Guidelines for the diagnosis and treatment of dementia and cognitive impairment in China” [17] and “Expert Consensus on Memory Examination in China” [18]. MoCA is now available in several Chinese versions including Beijing, Guangdong, and Changsha. The Beijing version has a sensitivity of 0.92, a specificity of 0.84, a test-retest reliability coefficient of 0.86, and an internal consistency reliability Cronbach α coefficient of 0.82 [19], and previous research [20] indicates that it is more suitable for assessing the cognitive function of older adults in Suzhou. According to the study conducted by Zhang et al. in nursing homes in southern China, the range of MoCA score for MCI among institutionalized older adults is 15–24 points [21], which was used in our study.
The 15-item geriatric depression Scale-15 (GDS-15)
The Chinese version of the 15-item Geriatric Depression Scale (GDS-15) was used. It has been validated in Chinese populations with a test-retest reliability coefficient of 0.728 and a Cronbach’s α coefficient of 0.79 for a score range of 0–15 [22]. The recommended cut-off score of 5 was used in our study to identify participants with depressive symptoms (GDS-15 Score ≥ 5) and those without (GDS-15 Score < 5) [23]. Higher scores indicate more depressive symptoms are present.
Procedures
Telephone invitations of the survey were made to all eligible residents of the four selected RCHs. Only those who consented to participate and signed a written informed consent were interviewed. The sociodemographic information questionnaire, MoCA and GDS-15 were filled out by trained researchers in an electronic form using a tablet or smartphone on site while interviewing participants. Two researchers were paired together - one was responsible for interviewing the patient and filling out the form, and the other was responsible for overseeing the input of data. They switched positions every other participant. The survey was conducted from January, 2017 to December, 2017.
Statistical analysis
SPSS version 23.0 software was used for statistical analyses. Univariate analysis was used to determine whether there was a significant difference between the mobile device users and non-users living in RCHs in the total MoCA score, the sub-scores of each dimension and the GDS-15 score. Parametric statistical tests were performed for normally distributed data and non-parametric tests for abnormally distributed data. After testing the assumptions for multivariate regression such as presence of linearity between the independent variables and the dependent variable and the absence of multicollinearity between the independent variables, a multivariate linear regression model was used to control for confounding factors such as age, sex, BMI, level of education, monthly income, frequency of socialization and underlying diseases. Mobile device use, age, sex, BMI, level of education, monthly income, frequency of socialization and type of underlying disease were used as the independent variables, and the total MoCA score and the sub-scores of each dimension as dependent variables respectively to analyze the impact of mobile device use on cognitive function. A binary logistic regression model was used to examine the impact of mobile device use on the level of depressive symptoms while adjusting for the confounding factors age, sex, BMI, level of education, monthly income, frequency of socialization and type of underlying disease. In the model, absence of depressive symptoms (GDS-15 score < 5) was assigned the value of “0” while presence of depressive symptoms was assigned the value of “1” (GDS-15 score ≥ 5). P < 0.05 indicates a statistically significant difference.