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Attention Score in Context
| Title |
Predicting cognitive function of the Malaysian elderly: a structural equation modelling approach
|
|---|---|
| Published in |
Aging & Mental Health, October 2016
|
| DOI | 10.1080/13607863.2016.1231172 |
| Pubmed ID | |
| Authors |
Hui Foh Foong, Tengku Aizan Hamid, Rahimah Ibrahim, Sharifah Azizah Haron, Suzana Shahar |
| Abstract |
The aim of this study was to identify the predictors of elderly's cognitive function based on biopsychosocial and cognitive reserve perspectives. The study included 2322 community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, biomarkers, psychosocial status, disability, and cognitive function. A biopsychosocial model of cognitive function was developed to test variables' predictive power on cognitive function. Statistical analyses were performed using SPSS (version 15.0) in conjunction with Analysis of Moment Structures Graphics (AMOS 7.0). The estimated theoretical model fitted the data well. Psychosocial stress and metabolic syndrome (MetS) negatively predicted cognitive function and psychosocial stress appeared as a main predictor. Socio-demographic characteristics, except gender, also had significant effects on cognitive function. However, disability failed to predict cognitive function. Several factors together may predict cognitive function in the Malaysian elderly population, and the variance accounted for it is large enough to be considered substantial. Key factor associated with the elderly's cognitive function seems to be psychosocial well-being. Thus, psychosocial well-being should be included in the elderly assessment, apart from medical conditions, both in clinical and community setting. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 109 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 15 | 14% |
| Student > Bachelor | 15 | 14% |
| Student > Ph. D. Student | 14 | 13% |
| Lecturer | 8 | 7% |
| Student > Doctoral Student | 7 | 6% |
| Other | 14 | 13% |
| Unknown | 36 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 18 | 17% |
| Psychology | 17 | 16% |
| Medicine and Dentistry | 14 | 13% |
| Social Sciences | 5 | 5% |
| Agricultural and Biological Sciences | 3 | 3% |
| Other | 11 | 10% |
| Unknown | 41 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 December 2017.
All research outputs
#20,656,820
of 25,374,917 outputs
Outputs from Aging & Mental Health
#1,555
of 1,886 outputs
Outputs of similar age
#251,723
of 326,128 outputs
Outputs of similar age from Aging & Mental Health
#40
of 50 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,886 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one is in the 4th percentile – i.e., 4% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,128 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.