salleh_2023_aim_iam_fim

2,040 responses from 170 respondents to 12 items.

About this table

Description12-item raw AIM-IAM-FIM implementation-outcome scale (1-5 Likert), Malay-language survey on a community-based health programme (MIICA/KOSPEN)
ReferenceSalleh H, Avoi R, Abdul Karim H, Osman S, Kaur N, Dhanaraj P (2023) Translation, Cross-Cultural Adaptation to Malay, and psychometric evaluation of the AIM-IAM-FIM questionnaire: Measuring the implementation outcome of a community-based intervention programme. PLoS ONE 18(11).
DOI10.1371/journal.pone.0294238
LicenceCC BY 4.0
Source datahttps://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0294238.s001

Size and shape

Responses2,040
Respondents170
Items12
Response categories5
Responses per respondent12
Responses per item170
Density1
LongitudinalFALSE

Classification

sampleProgram-based
measurement toolSurvey/questionnaire
item formatLikert Scale/selected response
primary language(s)may

Item text

This table has item text in the IRW: the wording administered to respondents, not just the response codes.

InstrumentAIM-IAM-FIM questionnaire (Malay Version): Acceptability of Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), Feasibility of Intervention Measure (FIM)
Mean words per item5
Mean characters per item32.333
Mean characters per response11.400
Flesch-Kincaid grade level7.600

Columns

iditemresp

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python:

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("salleh_2023_aim_iam_fim")
# Python
pip install irw

import irw
df = irw.fetch("salleh_2023_aim_iam_fim")

Version and provenance

IRW versionv393
Redivis datasetitem_response_warehouse_3 v7.0
Redivis dataset DOI10.57761/pqqn-pm43
Manifest pin for this IRW versionv7.0
Metadata sourceirw_meta v23.0