PMID- 35647258
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20220602
IS  - 2352-8273 (Print)
IS  - 2352-8273 (Electronic)
IS  - 2352-8273 (Linking)
VI  - 18
DP  - 2022 Jun
TI  - Challenges and measures to improve interviewers' bias in large-scale demographic 
      surveys in India: Some suggestions based on analysis of NFHS-4 data.
PG  - 101104
LID - 10.1016/j.ssmph.2022.101104 [doi]
LID - 101104
AB  - With increasing demand for more data at local level, the health surveys have 
      expanded both their coverage and areas of inquiry. To cater to this demand, the 
      sample size in National Family Health Surveys (NFHS) increased significantly and 
      thereby raised concerns regarding quality. The present paper attempts to 
      investigate the presence of interviewers' bias in the birth history data in 4(th) 
      round of NFHS in four states -Haryana, Odisha, Tamil Nadu and Maharashtra. The 
      paper suggests a practical procedure that can be used to promote judicious 
      supervision to minimize the non-sampling errors in future rounds of NFHS or other 
      large-scale demographic surveys. Findings show that the outlier-based approach 
      adopted in the paper helps in detecting the presence of interviewers' bias in the 
      enumeration of total children ever born as well as those born during 5 years 
      prior to the survey - two critical variables in demographic surveys. Among the 
      four study states, the extent of the bias was highest in Tamil Nadu. In fact, in 
      Haryana, the data was found to be free of any bias in the recording of the 
      occurrence of births in 5 years preceding the survey. It is suggested that it 
      should be feasible to employ the outlier-based approach early when fieldwork is 
      in progress, along with usual practice of generating field check tables. This 
      approach would have the potential to not only streamline the supervision but also 
      help salvage the data from any biasing effects. The biasing effects, if any and 
      found early during fieldwork can be rectified by suitably arranging the necessary 
      revisits to the respondents.
CI  - (c) 2022 The Authors.
FAU - Roy, Tarun Kumar
AU  - Roy TK
AD  - International Institute for Population Sciences, Mumbai, India.
FAU - Acharya, Rajib
AU  - Acharya R
AD  - Population Council, New Delhi, India.
LA  - eng
PT  - Journal Article
DEP - 20220424
PL  - England
TA  - SSM Popul Health
JT  - SSM - population health
JID - 101678841
PMC - PMC9136114
EDAT- 2022/06/02 06:00
MHDA- 2022/06/02 06:01
PMCR- 2022/04/24
CRDT- 2022/06/01 11:45
PHST- 2022/01/11 00:00 [received]
PHST- 2022/03/28 00:00 [revised]
PHST- 2022/04/19 00:00 [accepted]
PHST- 2022/06/01 11:45 [entrez]
PHST- 2022/06/02 06:00 [pubmed]
PHST- 2022/06/02 06:01 [medline]
PHST- 2022/04/24 00:00 [pmc-release]
AID - S2352-8273(22)00083-0 [pii]
AID - 101104 [pii]
AID - 10.1016/j.ssmph.2022.101104 [doi]
PST - epublish
SO  - SSM Popul Health. 2022 Apr 24;18:101104. doi: 10.1016/j.ssmph.2022.101104. 
      eCollection 2022 Jun.