Assessing the reactivity to mobile phones and repeated surveys on reported care-seeking for common childhood illnesses in rural India

Abstract

BackgroundTraditionally, health care-seeking for child illness is assessed through population-based and nationally representative demographic and health surveys (DHS) that are conducted once every five to seven years and are based on maternal recall. These maternal reports are subject to recall bias. Mobile phones (with the use of GPS technology) have the potential to constantly track movements of phone owners and provide high quality and more accurate data at a population level in low and middle income countries (LMICs) to assess the validity of maternal recall. We provided a group of mothers with smartphones installed with a location-aware application and visited them monthly to administer a survey questionnaire on care-seeking for diarrhoea, fever and cough with fever. This paper assesses for any reactivity to smartphones or repeated study contacts for measuring care-seeking and if this resulted in change in health care provider preference.MethodsWe enrolled 749 mothers from rural areas of Pune district in Maharashtra, India and randomly allocated them to one of three groups – a longitudinal phone group, a longitudinal control group and a cross-sectional control group. We collected baseline information from mothers, including individual and household demographic and socio-economic characteristics and care-seeking preferences for child illness. We followed up both longitudinal groups monthly and each cross-sectional sub-group once over a period of 6 months. At each follow up, we administered questions identical to those in the National Family Health Survey (NFHS) questionnaire to determine an episode of diarrhoea, fever or cough within the last 15 days, care seeking for the same, and the type of provider. The data were analysed using the χ2 test or Fisher Exact Test for categorical variables, or with the Kruskall-Wallis non-parametric test for continuous variables (due to the non-normal nature of the data). Multivariable joint models of group and visit time were analysed with logistic regression methods.ResultsAll three groups were similar in their socio-demographic characteristics at baseline. We did not observe any significant difference in care seeking for diarrhoea, fever or cough with fever between groups. Also, we did not observe any significant difference in proportion of children seeking care from the private sector.ConclusionsWe did not observe any reactivity in this study due to the presence of the phone (Hawthorne effect) or repeated study visits. The study also shows the potential of using GPS enabled smartphones to enrich DHS surveys in LMICs like India. However, further studies need to be conducted in other population groups before the findings can be generalised.

Defining and evaluating the Hawthorne effect in primary care, a systematic review and meta-analysis

“…A direct observation (e.g., HH studies) engenders the largest HE ( 56 ) but depends on the authority status of the observer ( 65 ). If the observation remains distant, but the subject or the investigator has to complete repeated measurements or questionnaires, his/her interest in the field of the questionnaire will tend to change his/her behavior or beliefs ( 13 , 24 , 35 , 95 ). This measurement bias is also described as “measurement reactivity” or “reactivity” ( 11 , 13 , 35 , 97 ).…”

“…Of the 74 selected reports in the definition branch, 15 were randomized controlled trials (RCTs) (25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39), two were not randomized controlled trials (40,41), three were studies nested in RCTs (42)(43)(44), seven were retrospective reanalysis or discussions of RCTs (23,24,(45)(46)(47)(48)(49), three were pilot studies prior to an RCT (50)(51)(52), and one was an RCT protocol (53). Further, there were 18 observational studies (54-71), 18 pre-post intervention studies or audits (21,22,(72)(73)(74)(75)(76)(77)(78)(79)(80)(81)(82)(83)(84)(85)(86)…”

Determinants and patterns of care-seeking for childhood illness in rural Pune District, India

“…Participants in the cross-sectional comparison group were also not provided phones and were divided into six subgroups, each followed up once over the six-month follow-up period ( Figure S1 in the Online Supplementary Document). Comparison groups were included to evaluate potential biases in reported care-seeking behavior among the phone group due to the presence of the smartphone or the repeated study contacts (see [29] and [30] for additional details). At each follow-up visit mothers were administered the NFHS module on childhood illness [5], which asks mothers whether their child experienced diarrhea, fever, or cough in the previous two weeks, whether any care was sought, and, if so, the sources from where care was sought.…”

Assessing the reliability of phone surveys to measure reproductive, maternal and child health knowledge among pregnant women in rural India: a feasibility study

“…Efforts to measure health practice, prevention and careseeking in India have most commonly been done via face-to-face survey methods, including the population-based National Family Health Surveys (NFHS) carried out approximately every 5–7 years 10 11. In addition to being costly and time-intensive, these population-based surveys are limited by lengthy recall bias 12.…”