| Literature DB >> 27894279 |
Etsuko Tadaka1, Ayumi Kono2, Eriko Ito3, Yukiko Kanaya2, Yuka Dai4, Yuki Imamatsu5, Waka Itoi6.
Abstract
BACKGROUND: Among older people in developed countries, social isolation leading to solitary death has become a public health issue of vital importance. Such isolation could be prevented by monitoring at-risk individuals at the neighborhood level and by implementing supportive networks at the community level. However, a means of measuring community confidence in these measures has not been established. This study is aimed at developing the Community's Self-Efficacy Scale (CSES; Mimamori scale in Japanese) for community members preventing social isolation among older people.Entities:
Keywords: Community networking; Elderly; Neighborhood; Scale development; Self-efficacy; Social isolation
Mesh:
Year: 2016 PMID: 27894279 PMCID: PMC5127097 DOI: 10.1186/s12889-016-3857-4
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Study response flow
| Population | GEN | CVOL |
|---|---|---|
| Registered |
|
|
| Responded |
|
|
| Valid |
|
|
Respondent characteristics
|
| ||
|---|---|---|
| GEN | CVOL | |
|
|
| |
| Sex | ||
| Female | 1800 (51.7) | 523 (60.9) |
| Age | ||
| <55 | - | 70 (8.2) |
| Living arrangement | ||
| Live alone | 431 (12.6) | 75 (8.8) |
| Years living in the city | ||
| <10 | 393 (11.3) | 22 (2.6) |
| Born in the city | ||
| Yes | 915 (26.4) | 226 (26.4) |
| Employed | ||
| Yes | 1199 (35.0) | 232 (27.2) |
CSES exploratory factor analysis
| GEN | CVOL | ||||||
|---|---|---|---|---|---|---|---|
| Factor I | Factor II | Communality | Factor I | Factor II | Communality | ||
| Community network | |||||||
| Q1 | I can participate in the activities or volunteer work of my neighborhood association. | 0.86 | 0.01 | 0.73 | 0.80 | 0.03 | 0.66 |
| Q2 | I can create an environment in which my neighbors can comfortably gather. | 0.80 | 0.11 | 0.75 | 0.76 | 0.10 | 0.69 |
| Q3 | I can encourage nearby neighbors to come out to gatherings. | 0.76 | 0.17 | 0.59 | 0.72 | 0.03 | 0.48 |
| Q4 | I can discuss my concerns about residents at neighborhood gatherings or community meetings held by local government. | 0.68 | 0.15 | 0.62 | 0.62 | 0.16 | 0.54 |
| Neighborhood watch | |||||||
| Q5 | I can check in on elderly neighbors if I do not see them for a few days. | 0.05 | 0.78 | 0.64 | 0.04 | 0.75 | 0.59 |
| Q6 | I can help older neighbors with grocery shopping, garbage disposal, and other chores. | 0.05 | 0.77 | 0.60 | 0.04 | 0.68 | 0.43 |
| Q7 | I can check in on neighborhood households where there are no signs of activity there. | 0.08 | 0.73 | 0.65 | 0.18 | 0.63 | 0.58 |
| Q8 | When I notice a person I do not know in the neighborhood, I can speak to them. | 0.07 | 0.62 | 0.45 | 0.14 | 0.65 | 0.45 |
| Contribution % | 0.24 | 0.28 | 0.52 | 0.32 | 0.22 | 0.54 | |
| Cumulative contribution % | 0.24 | 0.52 | 0.52 | 0.32 | 0.54 | 0.54 | |
Fig. 1CSES confirmatory factor analysis
CSES internal consistency and criteria-related validity
| GEN | CVOL | ||
|---|---|---|---|
| Basic statistics | |||
| All CSES: 8 items | Mean (SD) | 10.2 (5.2) | 13.8 (4.6) |
| Range | 0–24 | 0–24 | |
| Skewness | 0.01 | 0.07 | |
| Kurtosis | 0.15 | 0.22 | |
| Community network: 4 items | Mean (SD) | 5.7 (2.7) | 6.3 (2.5) |
| Range | 0–12 | 0–12 | |
| Skewness | 0.04 | 0.07 | |
| Kurtosis | 0.23 | 0.17 | |
| Neighborhood watch: 4 items | Mean (SD) | 5.4 (2.7) | 7.8 (2.4) |
| Range | 0–12 | 1–12 | |
| Skewness | 0.09 | 0.20 | |
| Kurtosis | 0.26 | 0.44 | |
| Internal consistency | |||
| All CSES: 8 items | Cronbach’s α | 0.90 | 0.87 |
| Community network: 4 items | Cronbach’s α | 0.84 | 0.79 |
| Neighborhood watch: 4 items | Cronbach’s α | 0.88 | 0.84 |
| Criterion-related validity | |||
| GCS-R | Ra | 0.80*** | 0.86*** |
| BSCS | Ra | 0.64*** | 0.66*** |
aPearson’s correlation, ***p < 0.001