Participants

A total of 120 pregnant women with an average age of 25 years (range 18 to 40 years) were interviewed. Two-thirds (66.9%) were from SNNPR (agrarian region) and the remaining 33.1% from Somali region (pastoral region). Two-thirds of the women (65.8%) did not complete primary school and three-quarters (75.0%) were housewives. Two-thirds of the women (65.8%) had at least one child living in their household.

Diet context

Most women (87.5%) reported that their food consumption the day before the interview was usual in terms of the types and amounts of foods consumed. Only 15 women reported having consumed an unusual diet; reasons included the fasting period just having ended, the previous day being a holiday, and having eaten with friends or relatives. Most respondents (83.3%) prepared their food at their own homes; only 16 reported that someone else in the household prepared their food and four reported that most of their food was prepared at someone else’s home.

The results from the feedback interviews with respondents, enumerators’ feedback, and FGDs with enumerators were grouped into three themes for reporting study results: feasibility and ease of use of the GDQS application, ease of remembering all the foods, beverages, and mixed dishes consumed the previous day during the open recall, and feasibility and ease of use of the set of 10 cubes to estimate quantities consumed at the food group level.

Feasibility and ease of use of the GDQS application (enumerator perspective)

Most respondent interviews were reported by enumerators as " easy” or " very easy” (85.8%) to collect data with the GDQS application, only eight interviews (6.7%) were reported as being “difficult " to collect, and none were reported as being “very difficult” (Fig. 1).

Fig. 1

Reported ease or difficulty of using the GDQS application for dietary data collection from the perspective of enumerators after each interview (n = 120)

Regardless of the rating of the ease of use of the GDQS application, all enumerators were asked to report the most difficult aspect of data collection using the GDQS application (Table 1). Even after probing, across all interviews completed, there were less than 50% of interviews (48.3%) for which no difficulties were reported by enumerators as occurring during the interview. The most reported difficulty by enumerators across the interviews completed was the respondent estimation of amounts consumed using the 3D cubes (24.2%). Some difficulties reported across interviews related directly to the functionality of the GDQS application (5.8%), language translation issues (2.5%), and the process of manually classifying foods, beverages, and ingredients not included in the GDQS database into the corresponding GDQS food group (1.7%). Enumerators reported that their perception of the respondents’ understanding of the interview questions was poor in only 3.3% of the total number of interviews completed.

Table 1 Difficulties identified in using the GDQS application to collect data after each interview (enumerator perspective)

When asked to rate their perception of the quality of the dietary data collected from the respondent using the GDQS application, three-quarters (73.9%) of the completed interviews were reported by enumerators to be of “good” or “excellent” quality. There were only three completed interviews for which enumerators considered the perceived data quality to be “poor” or “very poor” (Fig. 2).

Fig. 2

Perceived quality of the dietary data collected from the perspective of enumerators after each interview (n = 120)

During the FGDs, enumerators described the GDQS application interface as being user-friendly and intuitive. They mentioned several advantages of the GDQS application including the ease of the GDQS application installation, its ability to function offline, and fast submission of data when an internet connection was available. Enumerators appreciated that the application provided the necessary probes, which simplified obtaining the necessary details for each food, beverage, and ingredient consumed. Enumerators also appreciated that there was no data entry requirement after the completion of the fieldwork. Other benefits the enumerators mentioned included that there was no need to classify foods, beverages, and ingredients reported into the corresponding GDQS food group and that respondents did not need to understand the GDQS food groups to respond meaningfully to the interview questions. Enumerators appreciated the opportunity to add missing foods and beverages to the GDQS database during data collection and also reported that they were progressively able to collect data faster after gaining experience in collecting data with the GDQS application.

Enumerators noted, however, that the GDQS application had several bugs at the beginning of the data collection, all of which were subsequently fixed. They stressed that the GDQS application lacks a feature for saving foods, beverages, and mixed dishes encountered during data collection to the GDQS database for subsequent interviews. Some challenges were also encountered using the GDQS application in Somali and Amharic due to a lack of enumerator experience in typing these languages using a tablet keyboard. Additionally, in the Amharic version of the application, the list of food types did not appear in alphabetical order.

Enumerators’ recommendations for how to improve the GDQS application included extending the GDQS database to be even more comprehensive so more foods, beverages, and ingredients could benefit from automated classification into the correct GDQS food group, listing foods alphabetically in the Amharic version of the GDQS application, and simplifying the interview for rural communities. Enumerators also recommended developing a more extensive job aid with a description of the GDQS food groups and examples to help classify foods, beverages, and ingredients missing from the GDQS database.

Ease of remembering all foods consumed the previous day (respondent perspective)

When asked how easy or difficult it was to remember the foods, beverages, and ingredients consumed the previous day, most respondents (88.3%) reported that they found it “easy” or “very easy”. Only three respondents found it “difficult” or “very difficult” to remember all that they consumed the previous day (Fig. 3).

Fig. 3

Ease or difficulty of remembering all foods, beverages, and ingredients consumed the previous day from the perspective of the respondents (n = 120)

All respondents were asked to report what was easy and difficult to report during the open recall. The following reasons were reported for why it was easy to report foods, beverages, and ingredients consumed: 34 respondents (28.3%) always ate the same foods, 13 (10.8%) ate foods prepared at home, seven (5.8%) found the interview structure helpful, four (3.3%) only ate a few foods, and 62 (51.6%) considered the open recall “simple” (no reason provided). Only six respondents (5%) reported that there was anything difficult about reporting the foods consumed yesterday. When asked what was difficult, two respondents (1.7%) reported that they struggled to remember what they ate, two respondents (1.7%) found it difficult to estimate the amount consumed, one respondent (0.8%) mentioned that the food was prepared as a mixed dish, and one respondent (0.8%) mentioned that she consumed purchased foods.

Ease of remembering the foods, beverages, and ingredients consumed the previous day (enumerator perspective)

Enumerators discussed their experiences using the open recall during the FGDs. They reported that they had not encountered specific difficulties collecting data during the open recall portion of the interview. They commented that their sense was that respondents were able to report everything consumed the previous day. They also mentioned that asking respondents to recall foods consumed by mealtime, as prompted by the GDQS application, was helpful.

Ease or difficulty of using the cubes to estimate amounts consumed (respondent perspective)

More than half of respondents (55%) said it was “very easy” or “easy” to choose the cube that corresponded to the total amount (volume) of foods, beverages, and ingredients consumed for each GDQS food group. About one-fourth of respondents (23.3%) stated that it was “neither easy nor difficult”, while the remaining respondents (21.6%) said it was “difficult” or “very difficult” (Fig. 4).

Fig. 4

Ease or difficulty of the use of the set of 10 cubes to estimate quantities consumed at the food group level from the perspective of the respondents (n = 120)

All respondents were asked to provide open-ended feedback on the ease or difficulty of using the cubes. When probed, most respondents (64.2%) identified one or more challenges with the use of the cubes (Table 2). One-fifth of respondents (20.3%) found it difficult to use certain cube sizes (e.g., the smaller cubes were too small, the size distinction between some cubes was not visible, and some respondents consumed an amount of food that was greater than the largest cubes). Twenty respondents (16.3%) reported that they struggled to use the cubes to estimate the amounts of foods they had consumed, without providing specific reasons. An additional 15 respondents (12.2%) reported that it was difficult to estimate the amounts of specific foods they had consumed. Twelve respondents (9.8%) noted difficulty estimating individual consumption when eating from a shared plate. Four respondents (3.3%) reported that the shapes of the cubes do not correspond to the shapes of foods consumed and/or the shape of utensils used at home. Three respondents (2.4%) mentioned that it was difficult to estimate the amount of ingredients consumed in a mixed dish and one respondent (0.8%) mentioned that it was difficult to estimate the amounts of food consumed outside the home.

Table 2 Most difficult part about selecting the cube size for food group amount consumed (respondent perspective)

When asked whether there was a food or a set of foods for which selecting the cube size was especially difficult, 51 (42.5%) of respondents replied that there was. When asked to describe the types of foods considered difficult to estimate, respondents highlighted foods eaten in large (n = 6) or small amounts (n = 4), foods eaten from shared plates (n = 5), and ingredients of mixed dishes (n = 3). Examples of foods identified as being difficult to estimate included injera (n = 13), bread (n = 3), rice (n = 3), vegetables (n = 3), milk (n = 2), sauces (n = 2), sugar (n = 2), kocho (n = 2), biscuits (n = 1), and meat (n = 1).

Almost all respondents were able to report a reason why the cubes were easy to use. Two-thirds of the respondents related the ease of the use of the cubes to a type of food (44.1%) or to a specific food (22.5%) (Table 3). Liquid foods such as milk, juice, and tea (n = 29), foods eaten in large amounts (n = 8), solid foods (n = 5), foods prepared by the respondent herself (n = 3), and foods eaten in small amounts (n = 1) were considered easier to relate to a cube. Examples of foods considered easy to estimate included sugar, injera, eggs, rice, potatoes, and biscuits.

One-third of respondents (29.7%) related the ease of the use of the cubes to the property of the cubes; 15 respondents found the largest cubes were especially helpful, nine found it helpful that the cubes were each of a different size, and five mentioned that the cubes are like utensils used in their household.

Table 3 Easiest part about selecting the cube size for food group amount consumed (respondent perspective)

Most respondents (80.0%) consumed food from a shared plate the previous day. Among the 96 respondents who consumed food from a shared plate, half (49.0%) reported that they found it more difficult to select the cube size for the foods eaten from a shared plate, one-third (34.4%) reported that the level of difficulty was similar as for foods not eaten from a shared plate, and 16.7% found it easier to select the cube size for foods eaten from a shared plate than for foods not eaten from a shared plate.

Ease of using the cubes to estimate amounts consumed (enumerator perspective)

During the FGDs, enumerators reported that respondents liked the material of the cubes. Respondents could point at a cube, but respondents with poor literacy often needed additional guidance and time to understand the instructions. The smaller cubes were not considered useful by several respondents because they were perceived as too small, and some respondents attempted to select a cube size that was in between two cube sizes (which is not allowed).

Enumerators felt that it was easier to use the cubes for liquid foods. One enumerator stated that it was not intuitive to use cubes to estimate how much food was consumed. The enumerator explained that the shape of the cube does not correspond with commonly used household utensils.

When asked for their recommendations, enumerators offered suggestions to improve the use of cubes. These included changing the cube’s shape (e.g., to a round shape), adding a larger cube, adding a cube between cubes eight and nine which are the cubes with the largest size difference, using only four cubes instead of 10 while allowing for multiples and fractions of cubes, developing separate methods to estimate liquid and solid foods, developing a different method to estimate amounts of foods eaten from a shared plate, and acquiring a method of measuring ingredients.