Yoong 2020a.

Study characteristics
Methods	Study design: cluster‐RCT Length of follow‐up from baseline: 12 months Unit of allocation: centre Unit of analysis: child
Participants	Service type: centre‐based Operation: not reported Country (region): Australia (New South Wales (NSW) Country income classification: high Low‐SES sample: unclear Population description: NSW is a demographically and socioeconomically diverse state and contains approximately 387,245 children aged 3–6 years. Inclusion criteria: eligible centres were required to 1) be users of the partner provider’s ECEC online reporting software (HubWorks; HubCare ANZ) (∼15% of all ECEC services in NSW); 2) prepare and provide ≥ 1 main and ≥ 2 mid‐meals to children onsite; 3) make menu‐planning decisions onsite; and 4) have a menu planner (typically a cook) with sufficient English to engage with the intervention. Eligible children were required to 1) be aged 2–6 years; 2) be present at the centre on days of data collection; 3) have no dietary requirements preventing consumption of foods while in care; and 4) have parental consent. Exclusion criteria: centres were excluded if they outsourced menu‐planning decisions, catered exclusively for special needs children, or were run by the NSW Department of Education because such services had different operational and catering arrangements. Number of services randomised: 35 (groups not reported) Number of children randomised: 522 (288 intervention, 234 control) Characteristics Children Age: 4.6 years (SD 8.2 months) Gender (% female): 49.6% Ethnicity: not reported Parents Age (years): not reported Gender (% female): not reported Ethnicity: not reported Parent/family SES: not reported Method of recruitment: all ECEC centres were posted an invitation letter and information statement about the study 2 weeks before receiving a call from a research assistant to assess eligibility and obtain consent. These centres were asked to distribute information and consent forms to parents of children in the room with the highest number of children aged 2–6 years before the scheduled site visit. Consistent with previous approaches by the research team and to maximise consent, research assistants also approached parents at drop off on the day of the visit. Missing data/dropout: 14% (n = 31) of children at baseline were retained at follow‐up. Reasons for dropout: changeover of rooms and transition to school Characteristics of dropouts: not reported
Interventions	Programme name not reported Number of conditions: 1 intervention, 1 control Intervention duration: 12 months Intervention setting: ECEC Intervention strategies: Ethos and environment ECEC staff Training: a health promotion officer with experience using the program conducted a 3‐h training session with the supervisor and menu planner within each service. Training consisted of updating centres with sector‐specific nutrition guidelines, the main features of the online menu‐planning program and how to use them, and supporting the service to make changes to their menu.  Action plan: to generate service‐level support for use of the program, the health promotion officer also undertook action planning to ensure that allocated time and resources were provided to the menu planner(s) to access the program.  Support: ongoing support was provided via 2–4 phone calls to ECEC service cooks. The purpose of these calls was to provide technical support with using the program and overcome any reported barriers to using the program. The number of phone calls provided to each service was tailored depending on engagement with the program and menu compliance as assessed via analytics data collected via the program. Centres could also seek technical support via an online “help desk” feature available within the web‐based program. Service Audit and feedback: services were given access to a web‐based menu‐planning program, which undertook automated assessments on meals and snacks entered by menu planners and provided real‐time feedback on the number of servings of each of the core food groups and discretionary foods. The feedback also outlined whether the menu was compliant with that recommended by sector‐specific nutrition guidelines Resources: where menus were not compliant, the online program automatically provided ECEC centres with suggestions and recipes on how to modify the menus to meet guidelines. The online menu‐planning tool (“feedAustralia”) also included > 200 healthy recipes that met the guidelines for inclusion in ECEC menus as well as complete 1‐week sample menus that were compliant with guidelines. Centres were also provided with a portable tablet to facilitate access to the online program and recipes during food preparation processes. Reminders: ECEC centres were prompted fortnightly in the main software program to make changes to their menu to increase compliance if noncompliant, or if they had an incomplete menu entered in the online program. Partnerships Healthcare  Delivery: health promotion officers conducted training and provided support.  Intensity of intervention: 1 x 3‐h training; 2‐4 telephone calls Intervention delivered by: research team, healthcare staff Modality: face‐to‐face, telephone, online Theoretical basis: Technology Acceptance Model and Theoretical Domains Framework Description of control: usual care
Outcomes	Outcomes relating to child dietary intake: Vegetables intake, fruit intake, cereals and breads intake, meat and alternatives intake, dairy and alternatives intake, discretionary foods intake, diet quality (total) Number of participants analysed: Intervention baseline: 105‐112 Intervention follow‐up: 150‐183 Control baseline: 101‐108 Control follow‐up: 147‐151 Data collection measure: direct observation and short food survey Data collector: researcher and educator Validity of measures used: not reported Outcomes relating to child physical measures: BMI z‐score Number of participants analysed: Intervention baseline: 288 Intervention follow‐up: 268 Control baseline: 234 Control follow‐up: 215 Data collection measure: objectively measured (WHO) Data collector: researcher Validity of measures used: not reported Outcome relating to child language and cognitive performance: not reported Outcome relating to child social/emotional measures: not reported Outcome relating to child quality of life: Health rated quality of life Number of participants analysed: Intervention baseline: 94 Intervention follow‐up: 68 Control baseline: 69 Control follow‐up: 27 Data collection measure: parent proxy version of KIDSCREEN‐10 Data collector: parent Validity of measures used: validated Outcome relating to cost: Intervention delivery costs, cost per service, average cost‐effectiveness ratio, relative value index Number of participants analysed: not reported Data collection measure: micro‐costing and service questionnaire Data collector: researcher and nominated supervisors and menu planners Validity of measures used: not reported Outcome relating to adverse consequences: not reported
Notes	Funding source: supported by National Health and Medical Research Council (NHMRC) project grant APP1102943 and Cancer Council NSW (CCNSW) program grant PG16‐05. Pilot funding was also provided from the Hunter Cancer Research Alliance and the Priority Research Centre for Health Behaviour, University of Newcastle. Hunter New England Population Health, Hunter Medical Research Institute, and the University of Newcastle provided infrastructure funding. Healthy Australia Ltd provided in‐kind support for programming of the web program (“feedAustralia”). Healthy Australia Ltd co‐developed the web program and were members of the advisory group which supported decisions related to the design and delivery of the web‐based program.
Risk of bias
Bias	Authors' judgement	Support for judgement
Random sequence generation (selection bias)	Unclear risk	Centres were stratified by SES and randomly assigned after baseline data collection to the intervention or control group in a 1:1 ratio by an independent statistician using a random number function in Microsoft Excel 2010. However, for diet and quality‐of‐life outcomes, authors stated that "To minimize selection bias, research assistants blinded to center allocation sought consent for dietary observations from all parents. After obtaining consent, research assistants randomly selected 6–9 children per center for dietary observations because 1 individual could only observe ≤ 3 children each." However the random sequence generation is not detailed with regard to the 6‐9 children selected for dietary observation. As the random sequence generation for the primary outcome is not specified, the assessment is rated as unclear.
Allocation concealment (selection bias)	Low risk	Allocation was conducted by an independent statistician after baseline data collection.
Blinding of participants and personnel (performance bias) Diet outcomes	Unclear risk	ECEC staff and those delivering the intervention were aware of group allocation; however, parents were not explicitly informed of centre allocation. The outcome may have been influenced by lack of blinding.
Blinding of participants and personnel (performance bias) Physical outcomes	Low risk	ECEC staff and those delivering the intervention were aware of group allocation, though parents were not explicitly informed of centre allocation. However, the outcome is not likely to be influenced by lack of blinding.
Blinding of participants and personnel (performance bias) Quality of life outcomes	High risk	Parents were not explicitly informed of treatment allocation, but they were not blind to it, either. The outcome is likely to be influenced by lack of blinding.
Blinding of participants and personnel (performance bias) Cost	Unclear risk	ECEC staff and those delivering the intervention were aware of group allocation; however, parents were not explicitly informed of centre allocation. It is unclear whether the outcome is likely to be influenced by lack of blinding.
Blinding of outcome assessment (detection bias) Diet outcomes	Low risk	2 methods were used to obtain child diet outcomes: (1) children's dietary intake was observed by trained research assistants who were blinded to group allocation and (2) children's dietary intake was reported via survey by parents who were not explicitly informed of centre allocation, but they were not blind to it either. The outcomes included in the meta‐analyses were by blinded research assistants, therefore, we have assessed as low risk of bias
Blinding of outcome assessment (detection bias) Physical outcomes	Low risk	Children's height and weight were objectively measured by trained research assistants who were blinded to group allocation.
Blinding of outcome assessment (detection bias) Quality of life outcomes	High risk	Parents reported children's health‐related quality of life via interview using the KIDSCREEN‐10. Parents were not explicitly informed of centre allocation, but they were not blind to it either. The outcome measurement is likely to be influenced by lack of blinding. Study authors state that "First, the use of questionnaires completed by educators and parents to assess child diet quality and HRQoL [health‐related quality of life] is likely subject to recall and social desirability bias."
Blinding of outcome assessment (detection bias) Cost	Unclear risk	ECEC staff and those delivering the intervention were aware of group allocation. It is unclear whether the outcome is likely to be influenced by lack of blinding.
Incomplete outcome data (attrition bias) Diet outcomes	High risk	Study authors stated that "We attempted to undertake a cohort analysis; however, as expected there was high attrition of children, with only 14% (n=31) of children at baseline retained at follow‐up owing to changeover of rooms and transition to school." Due to the magnitude of missing data, the risk of bias was assessed as high.
Incomplete outcome data (attrition bias) Physical outcomes	High risk	Study authors stated that "We attempted to undertake a cohort analysis; however, as expected there was high attrition of children, with only 14% (n=31) of children at baseline retained at follow‐up owing to changeover of rooms and transition to school." Due to the magnitude of missing data, the risk of bias was assessed as high.
Incomplete outcome data (attrition bias) Quality of life outcomes	High risk	Study authors stated that "We attempted to undertake a cohort analysis; however, as expected there was high attrition of children, with only 14% (n=31) of children at baseline retained at follow‐up owing to changeover of rooms and transition to school." Due to the magnitude of missing data, the risk of bias was assessed as high.
Incomplete outcome data (attrition bias) Cost	Unclear risk	The number of services and participants that reported on this outcome is unclear.
Selective reporting (reporting bias)	Low risk	The outcomes reported in the paper were prespecified in the protocol paper.
Recruitment bias	High risk	Children were recruited over time. Study authors state that "We attempted to undertake a cohort analysis; however, as expected there was high attrition of children, with = only 14% (n 31) of children at baseline retained at follow‐up owing to changeover of rooms and transition to school."
Baseline imbalance	Unclear risk	Baseline differences between groups were not reported.
Loss of clusters	High risk	One cluster lost
Incorrect analysis	Low risk	Study authors stated that "For continuous outcomes, group differences were assessed through a group‐by‐time interaction in mixed‐effects linear regression models, which included a random effect to account for potential clustering. For dichotomous outcomes, a logistic regression adjusting for baseline scores and clustering was undertaken."
Contamination	Unclear risk	No evidence to make assessment
Other bias	Low risk	No clear other source of bias