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. Author manuscript; available in PMC: 2022 Aug 1.
Published in final edited form as: Aust Occup Ther J. 2021 May 6;68(4):336–344. doi: 10.1111/1440-1630.12732

Mealtime Behaviours of Young Children with Sensory Food Aversions: An Observational Study

Angela R Caldwell 1, Elise K Krause 1
PMCID: PMC8363574  NIHMSID: NIHMS1705113  PMID: 33955028

Abstract

Introduction:

Children with sensory food aversions are at risk for nutritional problems and occupational dysfunction during daily meals. To facilitate optimal occupational performance for children with sensory food aversions, it is critical that clinicians understand child behaviour and caregiver strategy use to manage child behaviour during meals. The purpose of this paper is to examine the reliability of a novel coding scheme, the Behavioural Mealtime Coding System, and identify associations among child acceptance of preferred and targeted foods, child food exploration, and caregiver use of strategies to manage child behaviour.

Methods:

Twenty-one children (aged 18-60 months) with sensory food aversions and their caregivers were recruited using a convenience sample. An observational video coding system was developed to code mealtime behaviour in 63 typical mealtime videos recorded by caregivers in the home environment. Inter-rater reliability, descriptive statistics, and bivariate correlations were calculated.

Results:

The Behavioural Mealtime Coding System demonstrated excellent inter-rater reliability (ICC = .95). Child bites of targeted foods were associated with mealtime duration (rs = .51, p =.02) and events of the child licking food (rs = .57, p =.007). Caregiver use of threats was positively associated with child age (rs = .48, p =.03) and negatively associated with caregiver education level (rs = −.49, p =.03).

Conclusion:

For children with sensory food aversions, increasing mealtime duration by embedding positive activities to encourage food exploration may improve acceptance of healthy targeted foods. Future research is needed to better understand the complex relationships among caregiver strategy use, mealtime duration, and child mealtime behaviour.

Keywords: feeding, behaviour, observational coding, parenting, preschool children

Proper nutritional intake is imperative for successful development in early childhood (Samuel et al., 2018); however, many children are not consuming well-rounded diets due to selective eating (Carruth et al., 2004). Selective, or picky, eating has been defined in a variety of ways, but includes an element of low dietary variety (Dovey et al., 2008). Among children, dietary selectivity is often based on the sensory characteristics of food, such as texture, smell or temperature. Approximately 50% of children demonstrate caregiver-reported selective eating behaviours by the age of two, many of whom (58%) will outgrow this behaviour pattern (Carruth et al., 2004; Mascola et al., 2010). However, young children (0-8 years) who demonstrate sensory food aversions (SFA) avoid food based on sensory characteristics (e.g. colour, texture, temperature) and are likely to demonstrate persistent selective eating because they also resist trying new foods and have strong food preferences (Chatoor, 2009; Toyama & Agras, 2016). Moderate to severe levels of food selectivity during early childhood have been shown to be associated with greater likelihood of conflicts regarding food, reduced growth, anxiety, depression, and attention deficits (Zucker et al., 2015). It is important to address these behaviours early in life to ensure proper nutritional intake during a critical time of brain development.

In addition, selective eating increases stress within the family unit and conflicts during mealtime (Luchini et al., 2017). Caregivers may use coercive strategies (e.g. threats, force feeding) to increase food acceptance, which can create a negative mealtime experience (Ramos-Paúl et al., 2014). Pressuring a child to eat novel foods is associated with poor outcomes, such as: 1) lower overall intake, 2) food dislikes and rejections, and 3) increased negative comments during mealtimes (Galloway et al., 2006; Jansen et al., 2017). Caregivers may also be tempted to use food rewards or bribes to encourage their child to try a novel or non-preferred food. This strategy undermines a child’s ability to build food preferences through exposure alone and may lead to negative consequences such as decreased preference for the targeted food and increased consumption of snacks (Vaughn et al., 2016).

Evidence-based strategies to improve dietary variety without using coercion include repeated exposure to foods (Anzman-Franca et al., 2012), non-food based positive reinforcement or praise (Cooke et al., 2011), and modeling of healthy eating behaviours (Fries & Van der Horst, 2019). Repeated exposure to novel foods in the absence of pressure to try the food has been shown to improve intake and preference for those foods among toddlers and preschoolers (Anzman-Frasca et al., 2012; Spill et al., 2019). Verbal praise for consuming healthy foods is also associated with higher intake of these foods (Luchini et al., 2017), without the negative effects of food-based reinforcement strategies. Access to positive role models during mealtime is also associated with increased acceptance of new foods and intake of healthier foods in children (Scaglioni et al., 2018). Essentially, caregivers should strive to maintain a responsive feeding environment that supports the child’s hunger cues and ensures a pleasant and structured feeding environment with few distractions (Black & Aboud, 2011; Satter, 2007). These environments tend to promote healthy eating behaviour and are inversely associated with selective eating in children (Finnane et al., 2017).

It is important to understand the relationships among caregiver mealtime strategies and child behaviours to facilitate positive mealtime experiences for the entire family (e.g., improved communication, decreased stress, and increased food exploration). From an occupational perspective, we are specifically interested in how children with SFA participate in the essential occupation of feeding when sharing a meal with family members. Because children with SFA often avoid any interaction (e.g., touching, playing, smelling) with novel or non-preferred foods, the purpose of this study was to describe their unique mealtime behaviours and identify associations among child and caregiver behaviours. Existing mealtime coding schemes, such as the Dyadic Interaction Nomenclature for Eating (DINE) and Mealtime Interaction Coding Scheme (MICS) did not meet the precise needs of our study (Stark et al., 2000, Dickstein et al., 1998). Specifically, we were interested in coding specific strategies and behaviours, whereas the MICS examines overall family functioning more broadly. Conversely, the DINE does provide a scheme for coding specific behaviours but does not specify between preferred and non-preferred foods and lacks codes for child food exploration (Poppert et al., 2015). Because targeted food acceptance and the ability to interact with and explore novel food are central to the clinical treatment of SFA, it was crucial that we used a system that reliably coded these behaviours.

The primary aim of this study was to describe the mealtime behaviours of young children with SFA and identify associations among child and caregiver behaviours. Therefore, we developed the Behavioural Mealtime Coding System (BMCS) to code child food exploration, child food acceptance by category, and caregiver strategy use. A secondary aim of this study was to test the interrater reliability of the BMCS. Reliably describing strategies that caregivers are currently using in the home environment may facilitate the design of family-centered interventions that address the needs of caregivers as well as children with selective eating patterns.

Method

Participants and Design

This observational study is a secondary analysis of data collected as part of a larger prospective pilot study (Caldwell et al., 2020). We recruited a convenience sample of 21 children (aged 18–60 months) and their caregivers from southwestern Pennsylvania in the United States of America through primary care offices, early intervention programs, and online (social media) advertisements. Eligible child participants met all four criteria for SFA as determined by an occupational therapist: 1) refuses foods based on sensory characteristics; 2) onset of food refusal occurs when novel foods are introduced; 3) eats preferred foods without difficulty; and 4) food refusal causes risk for nutritional deficiencies OR oral motor delay (Zero to Three, 2005). Clinical confirmation of SFA was determined using a structured mealtime observation and an in-depth caregiver interview. Eligible caregiver participants were fluent in English, aged 18 years or older, and a biological parent or legal guardian of the child participant. There were no specific exclusion criteria. All participants who completed the baseline phase of the pilot study were included in this analysis. This study was approved by the University of Pittsburgh Institutional Review Board (PRO15060533).

Data Collection Procedure

Caregivers were provided with a video camera and collaborated with a member of the research team to set it up in an unobtrusive position within their home. Movement patterns of the family, daily routines, and caregiver preferences were considered when identifying the best camera location for each family. The camera was positioned to capture “typical” meals in the space where the child ate most frequently. For example, if the child ate dinner on the floor while watching television, the camera was positioned to capture meals on the floor. To establish a baseline of mealtime behaviour and food acceptance under normal circumstances, caregivers were instructed to video-record 10 typical meals in the home over a two-week period. Instructions included turning the camera on at the beginning of the meal and stopping after the child was no longer actively participating in mealtime. All video data was stored locally on microSD cards, and caregivers completed a meal log of all meals recorded. This meal log included foods offered to the child during each meal to assist with coding. Caregivers were educated on the purpose of baseline data collection and were encouraged to continue offering meals to their child as they had prior to entering the study. Demographic data, such as gender, race, education, and household income, were also collected during this initial visit.

Development of a Video Coding System

Our research team (principal investigator and two occupational therapy graduate student research assistants) developed a video coding scheme to quantify outcomes of interest including child food acceptance, child food exploration, and caregiver use of behavioural management strategies (Table 1). Development of the coding system was influenced by a literature review of commonly used caregiver strategies to manage child mealtime behaviours and established mealtime and child-caregiver interaction coding schemes.

Table 1.

Behavioural Mealtime Coding System (BMCS)

Code Definition Example
Mealtime Duration Begins when child is seated at table or is provided with food and ends when the child walks away from food or stops participating. Child sits at table during meal for 20 minutes.
Child Food Acceptance
Bites preferred Child (or caregiver) places a bite of food categorised as preferred into child’s mouth and does not spit out. Child eats a bite of cracker (preferred).
Bites targeted Child (or caregiver) places a bite of food categorised as targeted into child’s mouth and does not spit out. Child eats a bite of broccoli (targeted).
Bites other Child (or caregiver) places a bite of food categorised as other into child’s mouth and does not spit out. Child eats a bite of bread (other).
Child Food Exploration
Touch Any event when the child’s hand or finger comes in contact with a food item, except when self-feeding with hands. Child pokes a piece of broccoli with finger.
Food play Any event when the child playfully interacts with their food. Child uses broccoli as “paintbrush” to draw with ranch dressing.
Lick Any event when the child’s tongue comes in contact with a food item without consumption. Child licks broccoli.
Caregiver Strategy Use
Labeled Praise Caregiver provides a positive evaluation of a specific attribute, product, or behaviour of the child. “You did a great job trying a bite of broccoli!”
Unlabeled Praise Caregiver provides a positive evaluation of the child, an attribute of the child, a nonspecific behaviour, or product of the child. “Great job, buddy!”
Generic Positive Reinforcement Caregiver verbalises a response (other than praise) to a desired behaviour in a positive manner and tone. “Yummy!” (in response to child taking a bite)
Direct Command Caregiver uses a declarative statement that contains an order or direction to a child to perform a specific mealtime behaviour(s). “Go sit down and eat.”
Threat Caregiver communicates an intent to inflict loss on child if they do not perform a specific behaviour. “If you don’t start eating, I’m turning off the TV.”
Bribe Caregiver persuades a child to act in a certain way by means of an outside inducement. “I’ll let you go outside if you take 3 more bites.”
Feeding Child Caregiver places food into child’s mouth either by hand or using a fork or spoon. Caregiver places a small piece of broccoli into the child’s mouth.
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The BMCS was developed within the Observer® XT software from Noldus. The Observer® XT allowed us to specify subjects, behaviours, and modifiers before or during an observation. Each behaviour coded in our system was rated by frequency of events, or number of times coded per meal. Additionally, this system allowed us to code observations by means of keystrokes or mouse clicks; each assigned to a timestamp to allow for advanced specificity. The Observer® XT allows coders to keep notes within the software and add or suggest new codes in real time based on mealtime observation. Mealtime duration was also calculated using the Observer® XT software based on the length of the mealtime video observation.

Child Food Acceptance

Bites of food accepted by children during video-recorded meals were categorised as preferred, targeted, or other prior to coding. In the pilot study, caregivers collaborated with an occupational therapist to develop a list of preferred foods, or those accepted >90% of the time when offered. They also developed a list of targeted foods, or those the child refused outright or spit out after one bite per caregiver report. Targeted foods were healthy foods that were offered frequently during mealtimes and prioritised as those caregivers would like their child to accept more frequently. The therapist asked questions about the child’s food preferences as well as family meal preparation and routines to facilitate brainstorming and identify potential foods for each list. Any food that was offered during video-recorded meals that did not appear on that specific child’s targeted or preferred food list was categorised as other. Bites of food were coded when a piece of food entered the oral cavity of the child and remained inside the mouth (i.e., the child did not spit it out; see Table 1).

Child Food Exploration

Child food exploration was also coded because children with SFA are often unable to tolerate sensory exploration of novel or non-preferred foods (Chatoor, 2009). Therefore, they have limited exposure and lessened ability to learn about the sensory characteristics of new foods, both of which have been shown to improve intake of novel foods (Coulthard & Sealy, 2017; Remington et al., 2012). Child behaviours coded as food exploration included touching, playing with, and licking food (see Table 1).

Caregiver Strategy Use

Behavioural management strategies were coded for all caregivers on the video who consented to participate in our study. Current evidence suggests that frequently used caregiver strategies to improve consumption of novel foods include positive reinforcement, verbal praise, bribes, threats, and force feeding the child (Cooke et al., 2011; Fries & Van der Horst, 2019; Podlesak et al., 2017). The Dyadic Parent-Child Interaction Coding System (DPICS: Eyberg et al., 2013) influenced the way in which we defined caregiver strategy use to increase objectivity. Review of this established coding system also informed our decision to categorise verbal praise into labeled praise (e.g., “great job trying a new food”), unlabeled praise (e.g., “nice work today”), and generic positive reinforcement (e.g., “tasty!”) as different types of verbal positive reinforcement. We also decided to add direct commands as potential caregiver behaviour management strategies based on our review of DPICS (see Table 1).

Video Coding Procedure

Using a random number list to minimise selection bias, we selected three of a possible 10 baseline meals per participant to be coded for this study, totaling 63 videos. Each family recorded at least eight baseline meals that demonstrated adequate quality and were included in a list to be randomised for coding. We chose to code three meals (described by families as “typical”) based on methods employed in similar studies (Spieth et al., 2001; Stark et al., 2000). A trained graduate research assistant was responsible for coding all 63 video-recorded meals. A second trained rater (undergraduate research assistant) coded one third of the videos (21) to determine inter-rater reliability of the coding scheme. As part of the training procedure, three sample videos were reviewed and coded by both raters; any inconsistencies observed were discussed by both raters under the guidance of the principal investigator until 100% agreement was reached for all disputed codes. Additionally, to improve coding transparency, each behaviour was followed by a note. For example, if a caregiver vocalised a direct command, the coder would key ‘direct command,’ followed by a caregiver quotation such as: “Go sit down and eat.”

Data Analyses

Inter-rater reliability of all behaviours included in the BMCS (see Table 1) was determined by calculating the intraclass correlation coefficient (ICC) and 95% confident intervals based on a single-rating (2,1), absolute agreement, 2-way random-effects model (Koo & Li, 2016). Prior to additional analyses, participant data from the three coded meals were collapsed into an average per meal total to ensure independence of observations, so that each participant was only represented in the analyses one time. Descriptive statistics were used to explore and describe observed mealtime behaviours. Bivariate correlations were calculated to identify potential associations between caregiver and child behaviour to inform hypotheses about how caregiver strategy use may influence child mealtime behaviours. Finally, we calculated bivariate correlations between demographic variables likely to influence mealtimes (i.e., child age, household income, caregiver education) and caregiver and child behaviour to identify potential confounders. All statistics were computed using IBM SPSS for Statistics, version 26.

Results

Child participants (n=21) ranged in age from 18 to 54 months and were predominantly male (76.1%) and non-Hispanic white (95.2%). Per caregiver report, five children had gastrointestinal issues, one had a diagnosis of Autism, and one had Sensory Processing Disorder; all children met the diagnostic criteria for SFA. Of 39 caregiver participants, 21 were females (mean age = 37 years) and 18 were males (mean age = 34 years). Two caregivers reported that their children were currently receiving occupational therapy (OT) services and one reported their child received OT services in the past (all due to concerns with feeding and sensory processing). No children enrolled in our study demonstrated swallowing difficulties or motor impairments that would influence mealtime behaviours. One third (7) of the children in this study were positioned in a highchair during mealtimes. Caregiver education level varied across families with most caregivers earning their bachelor’s degree or higher (87.1%). Most caregiver participants were employed full-time (61.5%) and most households earned an income greater than $100,000 (57%; see Table 2).

Table 2.

Demographics

Child Characteristics
n = 21		 n (%)
Gender
 Male 16 (76.1)
 Female 5 (23.8)
Age (mo)
 18-35 15 (71.4)
 36-60 6 (28.5)
Race/Ethnic group
 Non-Hispanic white 20 (95.2)
Diagnosis
 Autism 1 (4.8)
 Gastrointestinal issues 5 (23.8)
 Sensory Processing 1 (4.8)
Caregiver Characteristics
n = 39		 n (%)
Gender
 Male 18 (46.2)
 Female 21 (53.8)
Age (y)
 Range = 27 - 56
  Mean Female 34
  Mean Male 37
Race/Ethnic group
 Non-Hispanic white 37 (94.9)
Highest Education Completed
 Highschool 1 (2.6)
 Associates/Vocational 2 (5.1)
 Bachelors 19 (48.7)
 Graduate 16 (40.9)
Employment Status
 Employed full-time 24 (61.5)
 Employed part-time 3 (7.7)
 Working at home 4 (10.3)
 Retired 1 (2.6)
 Unemployed 2 (5.1)
Household Income ($)
 50,000– 75,000 3 (14)
 75,001 - 100,000 6 (29)
 >100,000 12 (57)
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Inter-rater Reliability of BMCS

Inter-rater reliability of the BMCS was found to be excellent for absolute agreement between our two raters with an ICC of .95 (95% confidence interval = .94-.96).

Descriptives

Among our sample, average mealtime duration for children was 17.5 minutes (SD = 5 minutes), with a range from 8 to 26 minutes average mealtime duration per participant. Food categorisation varied greatly by child; however, foods frequently categorised as targeted included proteins, vegetables, and fruit (e.g., grilled chicken, carrots, apples), whereas foods frequently categorised as preferred included starches and dairy products (e.g., cheese, crackers, bread). Children accepted, on average, 26 bites of food into their mouths per meal (SD = 15.7 bites), ranging from an average of 2 to 61 bites accepted during meals per participant. On average, most bites were of preferred foods (M = 18.2, SD = 13.4) and children accepted a much lower number of targeted foods per meal (M = 1.5, SD =2.5). Children most frequently explored food using touch (M = 3.2, SD=3.1; see Table 3). Inappropriate child behaviour codes of throwing food (M = 0.4) and spitting (M = 0.1) were used infrequently, with each code used for only 8 of the 21 children in our sample.

Table 3.

Average Frequency of Caregiver and Child Behaviours During Mealtime

Child (n = 21) Caregiver (n = 39)
Behaviour Mean SD Behaviour Mean SD
Total Bites 25.65 15.67 Labeled Praise 0.40 0.49
 Bites Preferred 18.21 13.35 Unlabeled Praise 1.17 1.08
 Bites Targeted 1.48 2.52 Positive Reinforcement 1.33 1.14
 Bites Other 7.00 8.47 Direct Command 8.76 6.58
Touch 3.22 3.09 Threat 0.49 0.85
Food Play 0.16 0.27 Bribe 0.75 1.03
Lick 1.44 2.31 Feeding Child 3.46 6.99
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In terms of strategy use, caregivers used direct commands more than any other strategy, with an average of nearly nine direct commands per meal (M = 8.8, SD = 6.6). While caregivers were observed to use different forms of positive reinforcement, they used generic positive reinforcement (M =1.3, SD = 1.1) and unlabeled praise (M = 1.2, SD = 1.1) more frequently than labeled praise (M = 0.4, SD = 0.5). As it relates to coercive caregiver strategies, bribes (e.g., “if you eat one bite of chicken, you can have a cookie”; M = 0.8, SD=1.0) were used more frequently than threats (e.g., “no hockey tonight if you don’t finish your dinner”; M = 0.5, SD = 0.9). Finally, although all children within this sample demonstrated the ability to self-feed, caregivers were observed to feed their child (by placing food into the child’s mouth) 3.5 times per meal, on average (SD = 7.0; see Table 3).

Associations

Child bites of preferred and other food were positively and significantly associated with mealtime duration (rs =.61, p =.004; rs =.44, p =.05) and total bites of food consumed (rs =.81, p <.001; rs =.59, p =.005). Child bites of targeted foods were positively and significantly associated with mealtime duration (rs = .51, p =.02) and events of the child licking food (rs = .57, p =.007). Notably, there were no significant associations observed between child food acceptance and caregiver behaviour management strategies (see Table 4). The only behavioural variable significantly correlated with demographic characteristics was caregiver use of threats, which demonstrated a positive association with child age (rs = .48, p =.03) and a negative association with caregiver education status (rs = −.49, p =.03).

Table 4.

Associations with Child Food Acceptance

Preferred Bites Targeted Bites Other Bites
 Mealtime Duration .60 ** .51 * .44 *
Child Food Exploration
Touch .30 .21 .31
Food Play −.09 .09 .18
Lick .10 .57 ** .25
Total Bites .81 ** .13 .59 **
Caregiver Strategy Use
Labeled Praise −.13 .09 −.39
Unlabeled Praise .06 .19 .08
Generic Positive Reinforcement .08 .13 .19
Direct Command −.03 .33 .21
Threat −.28 .31 .18
Bribe −.09 .32 .06
Feeding Child −.03 .20 .28
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Note.

**

indicates p <.001

*

indicates p <.05

Discussion

This study provides clinicians and researchers with insights about child food acceptance (targeted and preferred), child food exploration, and caregiver strategy use among children with SFA. It has also identified mealtime duration and child food exploration as potential predictors of targeted food acceptance within this population. We developed a reliable observational coding system to quantify child food acceptance, child food exploration, and caregiver behaviour management strategy use. Most food accepted during meals fell into the category of preferred, while children accepted very few, if any, bites of targeted foods. Children in our sample were most likely to explore food during meals by touching it, but unlikely to engage in food play. Lack of food play represents a meaningful target for occupational therapy intervention; sensory play, in combination with repeated exposure, has been linked to improved acceptance among preschoolers (Coulthard et al., 2017).

Caregivers most frequently used direct commands and feeding their child to encourage food acceptance and appropriate mealtime behaviour. Mealtime duration was positively associated with food acceptance in all categories, indicating that longer mealtimes may influence child acceptance of preferred and targeted foods. A child exploring food by licking it was also correlated with acceptance of targeted foods. It is important to note that in this study, targeted foods were foods that caregivers offered frequently, so children were likely exposed to these foods in the past. Although we did not measure prior exposure to targeted foods, repeated exposure may have influenced child willingness to try these foods in our sample.

The relationship between mealtime duration and food acceptance, specifically for bites of targeted foods, is likely complex. The average mealtime duration within this sample (17.5 minutes per meal) was notably shorter than those reported among young children (ranging from 19 to 26 minutes; Adamson et al., 2015; Crist & Napier-Phillips, 2001). This is likely due to unique manifestations of SFA, including the presence of inappropriate mealtime behaviours, inability to tolerate sensory characteristics of foods, and overall food refusal when not offered preferred foods (Chatoor, 2009). Young children with feeding disorders have been observed to demonstrate the extremes of mealtime duration among peers, falling either well below or well above average mealtime duration of children without feeding disorders (Litterbach, 2017). Therefore, it is likely that both meals that are too short (hence limiting opportunities for exposure) and those that are too long (with the potential to increase caregiver stress) are problematic. This is important to consider, as caregivers of young children with feeding disorders already demonstrate higher levels of stress than caregivers of children without feeding disorders (Fishbein et al., 2016).

Based on existing evidence and the results of our analyses, we recommend tracking mealtime duration for children with sensory food aversions to inform treatment planning. If a child’s mealtimes are consistently falling below average, examining potential causes of short duration (such as inappropriate child behaviour) and intervening to address problems and increase mealtime duration may be a promising strategy to improve acceptance of targeted foods. When increasing mealtime duration, it is important to incorporate exposure and exploration of healthy targeted foods (e.g., fruits, vegetables, lean proteins) to facilitate wider dietary variety, and not simply increased consumption of preferred foods. We would suggest that occupational therapy clinicians increase mealtime duration by incorporating positive strategies such as a regular mealtime routines and play-based exploration to mitigate negative mealtime experiences (Caldwell et al., 2020). Future experimental research with larger samples is warranted to parse out the complex relationships among mealtime duration, child behaviour, and child food acceptance during early childhood.

Our analyses also revealed a seemingly obvious association between total bites accepted by the child and the number of bites accepted of preferred and other foods. Interestingly, the number of accepted bites of targeted foods was not significantly correlated with the number of total bites. This signals that intervention to increase acceptance of targeted food may not impact overall food acceptance. This is a notable finding because it suggests that intake of targeted foods may not have a significant impact on total consumption, and consequently caloric intake. Therefore, interventions actively seeking to alter a child’s weight (either due to an underweight or overweight status) may be more likely to have an effect if the focus is placed on altering intake of foods considered preferred or neutral. However, the importance of increasing acceptance of healthy foods and promoting a wide dietary variety early in a child’s life cannot be understated, as preferences established during this sensitive period of development are known to persist (Mascola et al., 2010).

The observational nature of this study with data collection in the home environment strengthens the internal validity of our findings. The development of an objective coding system with excellent inter-rater reliability that includes child food exploration and the specification of preferred versus targeted food acceptance is a notable contribution of this work. Future studies are needed to establish content validity and determine concurrent validity of the BMCS with more established coding systems. Our ability to average data over multiple meals for each participant represents another strength of this study and enhances the reliability of our results. The potential for social desirability bias is important to acknowledge, as caregivers may have acted differently due to the presence of the camera and videorecording of meals. We limited this bias through unobtrusive camera positioning and limiting contact between the research team and participants during this baseline period. This study provides novel insights to clinicians about the mealtime practices and behaviours of young children with SFA and their caregivers.

This study also had several limitations that are important to acknowledge. To facilitate the generalisability of our results to the real world, we did not recommend any standardisation of mealtime procedures across families, which presents a threat to internal validity. Choosing not to exclude children who had received feeding therapy may have influenced both child and caregiver behaviour and is therefore a limitation of this study. Because mealtime routines are influenced by income, race, and cultural values (Horodynski et al., 2010), our small and homogenous sample limits external validity. It is promising that sociodemographic factors were not found to be associated with coded child behaviours, but additional research with more diverse samples is needed. Caregiver ratings of child mood and targeted food acceptance over time are also recommended measures for future trials to examine potential confounders and the robustness of the BMCS. Finally, the results reported are correlational and do not support causal inferences; they should be used to generate hypotheses and inform the design of future clinical trials.

Conclusion

Using a reliable observational coding system, we determined that mealtime duration and child food exploration were associated with child food acceptance within our sample. This descriptive study provides a glimpse into mealtimes within the home environment for young children who demonstrate sensory aversions to food. The BMCS is a novel coding scheme that may be used to code child and caregiver mealtime behaviours for children with limited dietary variety in future studies. We are currently examining the effects of enhancing child meals by systematically coaching caregivers to incorporate structured routines, positive reinforcement, and food exploration and play daily within the home environment. Future studies are needed to specify the observed relationship between mealtime duration and food acceptance, and to determine the optimal range of mealtime duration to promote targeted food acceptance among children with SFA.

Key Points for Occupational Therapy:

  1. The BMCS is a reliable tool for describing mealtime behaviours.

  2. Mealtime duration and food exploration are correlated with targeted food acceptance among children with SFA.

  3. Targeted food acceptance was not correlated with overall food acceptance.

Acknowledgements:

The authors would like to acknowledge Alison Juris for her early contribution to the development of the coding system and Emily Haus for her efforts in video coding to determine inter-rater reliability. We would also like to thank the support staff at Noldus for their early assistance in designing our coding scheme within the Observer® XT software.

Funding statement:

This research was supported by the School of Health and Rehabilitation Sciences Research Development Fund, the Department of Occupational Therapy at the University of Pittsburgh, and the National Center Medical Rehabilitation Research, National Institute of Child Health and Human Development/National Institute Neurological Disorders and Stroke, National Institutes of Health (K12 HD055931).

Footnotes

Conflict of Interest: The authors have no conflicts of interest to declare.

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