Effects of Parenting and Self-Efficacy on Diet, Family Mealtime and

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Theses and Dissertations

Summer 2023

Effects of Parenting and Self-E9cacy on Diet, Family Mealtime Effects of Parenting and Self-E9cacy on Diet, Family Mealtime

and Weight-Related Outcomes in African American Adolescents and Weight-Related Outcomes in African American Adolescents

Haylee Michele Loncar

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Recommended Citation Recommended Citation

Loncar, H. M.(2023).

Effects of Parenting and Self-E9cacy on Diet, Family Mealtime and Weight-Related

Outcomes in African American Adolescents.

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EFFECTS OF PARENTING AND SELF-EFFICACY ON DIET, FAMILY MEALTIME

AND WEIGHT-RELATED OUTCOMES IN AFRICAN AMERICAN ADOLESCENTS

Haylee Michele Loncar

Bachelor of Science

University of South Carolina, 2015

Master of Arts

University of South Carolina, 2019

Submitted in Partial Fulfillment of the Requirements

For the Degree of Doctor of Philosophy in

Clinical-Community Psychology

College of Arts and Sciences

University of South Carolina

2023

Accepted by:

Dawn K. Wilson, Major Professor

Nicole Zarrett, Committee Member

Ron Prinz, Committee Member

Allison Sweeney, Committee Member

Ann Vail, Dean of the Graduate School

iii

ABSTRACT

Despite substantial research and concern, adolescent overweight and obesity

continues to be a significant public health problem. Theory based on developmental

literature emphasizes the role of adolescent self-regulatory factors, like self-efficacy, in

health behavior engagement and weight-related outcomes. There is also extensive

literature that highlights parents’ role in promoting self-regulatory development through

warm and responsive behaviors and practices. However, few studies have considered

longitudinal associations and changes in weight-related outcomes over time, as well as

moderated effects by parenting. This study assessed longitudinal associations between

adolescent self-efficacy parenting factors and adolescent BMI, diet, and family mealtime

to fill gaps in current literature. It was hypothesized that greater improvements in

adolescent self-efficacy would be associated with greater improvements over time on

adolescent weight-related outcomes (improved zBMI, increases in fruit and vegetable

intake, decreases in fat intake and kilocaloric intake, and improvements in family

mealtime). Moreover, it was hypothesized that increases in warm, responsive parenting

(more responsive, greater responsibility) would be associated with greater improvements

over time in adolescent BMI, diet, and family mealtime outcomes. Conversely, increases

in parental demandingness and monitoring were hypothesized to be associated with less

desirable BMI, diet, and family mealtime outcomes over time. A second aim of this study

was to investigate the moderating effects of parenting factors on adolescent self-efficacy

in predicting adolescent zBMI, diet, and mealtime related outcomes. It was hypothesized

that increases in responsive parenting (responsiveness, parental responsibility) would be

related to a more positive association between self-efficacy and adolescent healthier

outcomes, while more demanding parenting (demandingness, parental monitoring) would

be related to a negative association between self-efficacy and adolescent BMI, diet, and

family mealtime outcomes over time. This study used longitudinal data from families

enrolled in the Families Improving Together (FIT) for Weight Loss trial (n = 241;

adolescent age

= 12.83 years; 64% female; M

BMI%

= 96.6%) to test these associations and

interactions from baseline to 16-weeks. The hypotheses for the study were only partially

supported. There were no significant associations between adolescent self-efficacy and

weight-related outcomes. Significant main effects demonstrated temporal stability of

some variables. Parental responsiveness was positively related to kCal (Estimate=127.37,

SE = 63.65, p<0.05) and fat intake (Estimate=6.15, SE = 2.46, p<0.01), which was

contrary to the hypothesized direction. However, as expected, parental responsiveness

was positively associated with frequency of family meals (Coefficient=0.43, SE = 0.10,

p<0.01) and parental responsibility was positively associated with quality of family meals

(Coefficient=0.35, SE = .18, p<0.05). Significant two-way interactions with time were

also found. Parental responsibility over time was related to zBMI in an unexpected

direction (Estimate=0.09, SE = 0.02, p<0.01), and parental monitoring over time was

related to zBMI in an unexpected direction (Estimate=-0.10, SE = 0.02, p<0.01).

However, parental responsiveness (Coefficient=0.16, SE = 0.08, p=0.04) and parental

demandingness (Coefficient=-0.25, SE = 0.08, p<0.01) both predicted quality of family

mealtime over time in the expected direction. Results also indicated three significant

three-way interactions that were in unexpected directions. Specifically, three-way

interactions between adolescent self-efficacy, time, and parental demandingness on kCal

intake (Estimate=62.83, SE = 28.13, p<0.05) and fat intake (Estimate=3.09, SE = 1.09,

p<0.01) revealed unexpected findings, such that self-efficacy was associated with greater

kCal/fat intake among adolescents with parents who practiced low demandingness and

lower kCal/fat intake among those with parents who practiced high demandingness.

Additionally, there was a significant three-way interaction between adolescent self-

efficacy, time, and parental responsibility for their adolescent’s diet in predicting

frequency of family meals (Estimate=0.12, SE =0.04, p<0.01), such that lower self-

efficacy was associated with more frequent family meals for adolescents with highly

responsible parents during baseline (0-weeks) and post-group (8-weeks). Results from

this study may provide directions for future research and have implications for adolescent

overweight/obesity prevention and interventions through family-based programs.

Keywords: Parenting, Adolescent self-efficacy, Family mealtime, African American

TABLE OF CONTENTS

Abstract .............................................................................................................................. iii

List Of Tables .................................................................................................................. viii

List Of Figures ................................................................................................................... ix

Chapter One: Introduction ...................................................................................................1

1.1 Theoretical Framework ........................................................................................8

1.2 Prior Literature on Self-Efficacy, Adolescent BMI,

Diet, and Family Mealtime .......................................................................................12

1.3 Prior Literature on Parenting, Adolescent BMI, Diet, and Family Mealtime ....17

1.4 Prior Literature on Parenting, Adolescent Self-Efficacy, Adolescent BMI,

Diet and Family Mealtime ..........................................................................................21

1.5 Study Purpose and Hypotheses ..........................................................................27

Chapter Two: Methods ......................................................................................................32

2.1 Participants .........................................................................................................32

2.2 Study Design ......................................................................................................33

2.3 Procedures ..........................................................................................................33

2.4 Measures .............................................................................................................35

2.5 Data Analytic Plan .............................................................................................41

2.6 Preliminary Analyses and Assumptions .............................................................43

2.7 Missing Data ......................................................................................................45

Chapter Three: Results .......................................................................................................47

3.1 Correlation Analyses ........................................................................................47

vii

3.2 Primary Outcome zBMI ...................................................................................48

3.3 Secondary Outcome kCal Intake .....................................................................53

3.4 Secondary Outcome Fat Intake ........................................................................53

3.5 Secondary Outcome Fruit Intake .....................................................................58

3.6 Secondary Outcome Vegetable Intake .............................................................58

3.7 Secondary Outcome Frequency of Family Mealtimes .....................................61

3.8 Secondary Outcome Quality of Family Mealtimes .........................................64

Chapter Four: Discussion ...................................................................................................69

4.1 Findings Associated with Weight-Related Outcomes ....................................71

4.2 Findings Associated with Dietary Outcomes ..................................................74

4.3 Findings Associated with Frequency and Quality of Family Mealtime .........77

4.4 Study Limitations and Strengths .....................................................................79

4.5 Implications and Future Directions ..................................................................81

4.6 Conclusion .......................................................................................................82

References ..........................................................................................................................84

viii

LIST OF TABLES

Table 2.1 Descriptive Baseline Data .................................................................................34

Table 2.2 Predictor Means and Standard Deviations .........................................................40

Table 2.3 Model Building ..................................................................................................44

Table 3.1 Correlation Analysis ..........................................................................................49

Table 3.2 Hierarchical Approach – zBMI .........................................................................50

Table 3.3 Outcome Analyses - zBMI ................................................................................50

Table 3.4 Hierarchical Approach – kCal ...........................................................................54

Table 3.5 Outcome Analyses- kCal ...................................................................................54

Table 3.6 Hierarchical Approach – fat ...............................................................................56

Table 3.7 Outcome Analyses - fat......................................................................................56

Table 3.8 Hierarchical Approach – fruit ............................................................................59

Table 3.9 Outcome Analyses – fruit ..................................................................................59

Table 3.10 Hierarchical Approach – vegetable ..................................................................60

Table 3.11 Outcome Analyses– vegetable .........................................................................60

Table 3.12 Hierarchical Approach – frequency of family mealtime .................................62

Table 3.13 Outcome Analyses– frequency of family mealtime ........................................62

Table 3.14 Hierarchical Approach – quality of family mealtime ......................................66

Table 3.15 Outcome Analyses– quality of family mealtime .............................................66

LIST OF FIGURES

Figure 1.1 Model of Expected Relationships .....................................................................31

Figure 3.1 Parental Responsibility x Time for zBMI ........................................................52

Figure 3.2 Parental Monitoring x Time for zBMI .............................................................53

Figure 3.3 Self-Efficacy x Parental Demandingness x Time for kCal ..............................56

Figure 3.4 Self-Efficacy x Parental Demandingness x Time for Fat .................................58

Figure 3.5 Self-Efficacy x Parental Responsibility x Frequency of Family Mealtime ......64

Figure 3.6 Parental Responsiveness x Time for Quality of Family Mealtime ...................68

Figure 3.7 Parental Demandingness x Time for Quality of Family Mealtime ..................69

CHAPTER ONE

INTRODUCTION

Childhood overweight and obesity remain a significant health concern in the

United States (Ogden, Carroll, Lawman, et al., 2016). This problem is particularly salient

in African American families, where nearly 40% of adolescents are overweight or obese

(Ogden, Carroll, Kit, et al., 2016). Persistence of childhood obesity prevalence is

alarming as it is predictive of numerous serious health conditions, including hypertension

and diabetes (Kohut et al., 2019). Continued evaluation of factors that may contribute to

adolescent obesity and related health disparities is needed to determine efficacious

prevention and treatment approaches. One relationship that has been studied involves that

connections between cognitive factors and health outcomes in adolescents. Specifically,

self-regulatory skills, including self-efficacy, have gained scholars’ attention for their

association with adolescents’ weight related outcomes.

Recent studies have highlighted the associations between adolescents’ perceived self-

efficacy for health outcomes such as BMI and diet, as well as family mealtime (Bandura,

2004; Dallacker et al., 2018, Hill et al., 11998, Milleret al., 2020; Robson, Allen, &

Howard, 2020). Self-efficacy is one’s belief in his or her ability to engage in a specific

action to reach an anticipated outcome and is considered a key predictor of intentions and

behaviors (Bandura 1986, 1997). Research shows associations among adolescent’s self-

efficacy beliefs and engagement in specific actions, such as health behaviors (Greve et

al., 2001). Similarly, self-regulation relates to an individual’s ability to regulate his or her

own behaviors, cognitions, and emotions (Baker et al., 2019). Literature suggests that

these two concepts are closely related as emergent self-efficacy triggers self-regulatory

processes, such as goal-setting and self-monitoring (Bandura, 2004; Zimmerman, 2000).

A recent review highlights these associations between self-regulatory processes and

weight-related outcomes and found that greater self-efficacy and self-regulation are

largely related to more desirable health outcomes, such as healthier diet or healthier body

mass index (BMI) in youth (Robson et al.,2020). Some research also established a link

between adolescent self-efficacy and self-regulation and family mealtime (Dallacker et

al, 2018; De wit et al, 2013). Examining these relationships in adolescents is particularly

important, as adolescence is a critical developmental period where youth become more

independent and cultivate self-efficacy (Keshavarz & Mounts, 2017).

Sufficient evidence exists in broader literature to suggest marked relationships between

self-efficacy and BMI and diet in adolescents (Dowda et al., 2020; Pajares, 2006; Schunk

& DiBenedetto, 2019). Namely, cross-sectional findings suggest that greater self-efficacy

is associated with healthier adolescent outcomes, such as healthier BMI and dietary

intake (Prioste et al., 2017; Steele et al., 2011a). However, few studies have investigated

how associations between these variables may change over time. One recent study

evaluated longitudinal effects of a self-efficacy intervention aimed to increase fruit and

vegetable intake in adolescents (Luszczynska et al., 2016). Luszczynska and colleagues

(2016) found that adolescents who received interventions based on behavioral change

principles – aimed to increase planning and self-efficacy for fruit and vegetable

consumption – demonstrated increases in fruit and vegetable intake after 14 months

(Luszczynska et al., 2016). However, the authors found no relationship between the

intervention and adolescents’ body weight. In addition to suggesting that dietary self-

efficacy is a promising target for improving health outcomes, this past study suggests that

changes in dietary self-efficacy are related to changes in health outcomes over time.

Specifically, increases in dietary self-efficacy may be associated with increases in

healthful dietary intake and greater weight-loss. Therefore, this study will assess the

relationship between adolescent self-efficacy and BMI and diet over time in an entirely

overweight, African American adolescent sample.

Despite significant literature on the relationships between self-efficacy and BMI

and diet outcomes, there is little research on the relationships between self-efficacy and

family mealtime. Existing literature has suggested that greater self-efficacy is established

through increasing practical skills in an area (Bandura, 1977). For instance, engagement

in food-related behaviors such as grocery shopping and meal preparation may increase

practical skills, thereby increasing self-efficacy. In turn, engagement in these meal-

related behaviors may lead to increased engagement and enjoyment of family meals

(Dallacker et al., 2018; Hill et al 1998). One study found a direct relationship between

self-efficacy and family mealtime. Woodruff and colleagues (2013) found that children

and adolescents with higher self-efficacy had greater family dinner frequency when

compared to children with lower self-efficacy (Woodruff & Kirby, 2013). The study

assessed these relationships in primarily white participants and is one of the only known

studies to assess these direct relationships. The present study will fill a gap in literature

to assess the relationship between self-efficacy and family mealtime outcomes in

overweight, African American families.

In addition to self-efficacy, parenting factors, such as parenting style and feeding

practices, have also been associated with adolescent health and related outcomes.

Specifically, past research highlights the relationship between parenting style and feeding

practices on adolescent BMI and weight-related outcomes (Loncar et al., 2021; Pearson et

al., 2012; Shloim et al., 2015a; Thomson et al., 2020; Vaughn et al., 2016). More so,

parenting styles and parenting practices have been linked to family mealtime behaviors

(Ardakani et al., 2023; Kitzman et al., 2010; Wilson et al., 2021). Parenting styles are

categorized by the responsiveness and demandingness that parents practice with their

children (Baumrind, 1971; Maccoby & Martin, 1983). Authoritative (high

responsiveness, high demandingness) and authoritarian (low responsiveness, high

demandingness) are commonly considered in literature. Authoritative parenting has been

associated with a broad range of desirable health outcomes, including healthier zBMI and

more nutritious dietary intake, in adolescents as it balances age-appropriate expectations

with warm and supportive interactions (Berge et al., 2010a; Blissett & Bennett, 2013a;

Burton et al., 2017; Franchini et al., 2011; Kiefner-Burmeister & Hinman, 2020; Loncar

et al., 2021c; Shloim et al., 2015b; Sleddens et al., 2008). However, most of this research

is cross-sectional in design and examines these associations in younger population.

Additionally, authoritative parenting style has been associated with increased family meal

frequency (Ardakani et al., 2023; Wilson et al, 2021). Though there is limited literature

outlining associations with parenting style and quality of family mealtime, concepts of

authoritative parenting (e.g. responsiveness) map onto factors for higher quality meals.

Though experts suggest that parenting style is generally a time-stable construct,

insufficient longitudinal data exists to conclude parenting style does not change over time

(Darling & Steinberg, 1993). The current study aims to add to existing literature by

providing a longitudinal perspective on the changes over time and moderating effects of

parenting and self-efficacy on adolescent BMI and diet.

Parental feeding practices, which involve parents’ behaviors that affect their

child’s eating, are also a popular metric for understanding the relationship between

parenting behaviors and adolescent BMI and diet, as well as family mealtime (Ardakani

et al., 2023; Birch et al., 2001a; Gevers et al., 2014; Wilson et al., 2021). These practices

vary in their perceived responsiveness and demandingness, where parental responsibility

for their adolescent’s diet highlights areas of support around diet, while parental

monitoring for adolescent dietary intake involves aspects of control surrounding the

adolescent’s diet. Unlike parenting style, experts suggest that parenting practices, such as

parental responsibility and monitoring of adolescent diet, may fluctuate over time

(Baumrind, 1971; Darling & Steinberg, 1993). However, the bulk of existing literature is

cross-sectional in design, limiting the interpretation of longitudinal relationships and

changes over time among parenting factors and adolescent BMI and diet (Blissett, 2011;

Loncar et al., 2021; Rollins et al., 2016; Shloim et al., 2015a; Wilson et al., 2002). More

so, limited research exists that examines the association between parental feeding

practices and family mealtime frequency or quality. Holland and colleagues (2014)

investigated changes in parental feeding practices over time in their family-based

behavioral intervention to improve child BMI (n=170, 7 -11 years). The researchers

found that increases in perceived parental responsibility for adolescents’ diet was

associated with decreases in child zBMI (Holland et al., 2014). These results highlight

the relationship between parenting factors and adolescent health and suggest that changes

in parenting are followed by changes in adolescent health. Recent cross-sectional

literature provides additional support that feeding practices, responsibility and

monitoring, are associated with adolescent weight-related outcomes (Schmidt et al.,

2017; Shloim et al., 2015a). Namely, greater parental responsibility has been related to

healthier adolescent BMI, while greater parental monitoring has been associated with

higher adolescent BMI (Burton et al., 2017; Holland et al., 2014; Schmidt et al., 2017;

Towner et al., 2015). Given the limitations of cross-sectional evidence, the present study

will assess these parenting measures using a longitudinal design and focus on evaluating

how changes overtime impact adolescent BMI, diet, and family mealtime.

While literature adequately outlines the direct associations between adolescent

self-efficacy and health outcomes and parenting factors and health outcomes, less

research has focused on how parenting style and feeding practices can modify the

relationship between adolescent self-regulatory factors on adolescent BMI, diet, and

family mealtime. Theoretical and developmental literature has emphasized that warm and

responsive parenting style and practices promote key developmental tasks such as

building self-efficacy, self-regulation, and autonomy in adolescents (Biglan et al., 2012;

Greve et al., 2001; Keshavarz & Mounts, 2017; Smetana et al., 2006). Parents may foster

this development through both general parenting styles, such as warm and responsive

authoritative parenting, as well as specific parental feeding practices that map onto those

dimensions. Specifically, parents may support dietary self-regulation and self-efficacy

through appropriate engagement with their adolescent. Promotion of these cognitive

factors is essential as research suggests that self-regulation and self-efficacy are critical

predictors of health behavior engagement and weight-related outcomes (Burns, 2019;

O’Dea & Wilson, 2006; Robson, D.A. et al., 2020). Conversely, parenting characterized

by low responsiveness (i.e. authoritarian parenting) or is not autonomy-supportive may

impede the development of these skills, relating to poorer BMI and diet in adolescents

(Kipp et al., 2021; Loncar et al., 2021; Shloim et al., 2015; Sleddens et al., 2011; Wilson

et al., 2017). Additionally, literature shows that more supportive parental feeding

practices, such as providing adolescents autonomy for healthy meals, encourage

adolescent self-efficacy and self-regulation development and may therefore modify the

relationship between self-efficacy and BMI and diet in adolescents (Holland et al., 2014;

LeCuyer et al., 2011). Warm and responsive parenting may also be related to the

frequency of family meals and the perceived quality of those meals (Ardakani et al.,

2023; Wilson et al., 2021). Therefore, the current study will investigate the potential

interaction of parenting factors and adolescent self-efficacy in predicting adolescent

weight-status, dietary outcomes, and family mealtime in overweight, African American

adolescents.

In sum, parenting factors play an important role in adolescent development

domains, including self-regulation and self-efficacy development (Biglan et al., 2012;

Tabak & Zawadzka, 2017; Wilson et al., 2017). Specifically, familial influences such as

parenting style (responsiveness and demandingness) and feeding practices relate to

adolescent’s self-efficacy and may be linked to weight-related outcomes such as BMI,

diet, and family mealtime outcomes (Gestsdottir & Lerner, 2008; Keshavarz & Mounts,

2017; Masten, 2004; Schunk & Pajares, 2002). Thus, this proposed study will examine

the moderating effect of parenting factors on self-efficacy in predicting adolescent BMI,

diet, and family mealtime outcomes in overweight, African American adolescents.

1.1 Theoretical Framework

Family systems theory. The Family Systems Theory (FST) highlights the

importance of the family system in understanding and explaining individual behavior

(Broderick, 1993). According to FST, families’ functionality hinges on the types of

interactions members have with each other. Positive interactions, such as warm and

supportive parent-adolescent exchanges, have been associated with a number of desirable

health outcomes, including improvements in adolescent overweight and obesity and

increasing frequency and quality of family meals (Biglan et al., 2012; Kitzman-Ulrich et

al., 2010; Parletta, Peters, Owen, Tsiros, & Brennan, 2012; Shloim et al., 2015; Wilson et

al., 2021). Authoritative parenting is one parenting factor that promotes a positive

environment through parents’ developmentally appropriate expectations and warmth.

This type of environment may foster the development of key psychological factors, such

as self-regulation and self-efficacy, and thereby influence adolescent health. In fact,

adolescents with authoritative parents typically experience more desirable health

outcomes, such as having a healthier weight-status or consuming a more nutritious diet.

Additionally, authoritative parenting may have impacts on family mealtime frequency

and quality, whereby responsive parenting relates to more frequent family meals that

adolescents enjoy. These effects, in turn, can affect child and adolescent weight-related

outcomes (Berge et al., 2014; Berge et al., 2015; Dallacker et al., 2019).

As parents shape their adolescent’s home environment, they may influence

several relationships and outcomes. Namely, authoritative parenting style and practices

may act as a buffer for at-risk adolescents and undesirable health outcomes. For instance,

Connell and Francis (2014) examined the moderating effects of parenting on the

longitudinal relationship between child self-regulation and weight-status. The authors

found that warm and responsive parenting led to a stronger relationship between self-

regulation and healthier weight-status in boys when compared to peers with less

authoritative parents. While literature specifically examining this type of interaction is

limited, the FST highlights the potential influence that parents have on the home

environment and may consequently influence BMI and diet in adolescents. Specifically,

FST suggests that parents’ overall ability to shape environmental factors results in their

influence in numerous contexts, including the relationship between adolescent self-

efficacy and health outcomes (e.g., diet and weight related outcomes). Importantly,

parenting practices may change over time. These changes, according to FST, may

precipitate changes in adolescent BMI and diet (Boele et al., 2020). Changes in parenting

practices, such as parental feeding practices, may also affect both quantity and quality of

family meals (Ardakani et al., 2023). This present study aims to specifically assess how

changes in parenting factors relate to changes in adolescent BMI, diet, and family

mealtime over time. The FST framework highlights how engaging the family system in

weight-related interventions can promote positive health outcomes through addressing

the parenting factors. This framework suggests that changes in parenting factors, such as

increased parental warmth, responsiveness, and responsibility, may result in

improvements in health behavior changes in adolescents. Additionally, more responsive

parents may initiate more family meals, creating a positive climate for familial

interactions and fostering opportunities for health behavior changes. Higher

responsiveness and responsibility that is characteristic of authoritative parenting may also

influence the quality of mealtime, as adolescents may perceive the supportive mealtime

environment to be more enjoyable. The FST framework is essential in considering

interactions between parenting factors and adolescent self-efficacy in predicting

adolescent BMI, diet, and family mealtime over time. Namely, this framework

emphasizes that parenting factors may interact with various aspects of adolescent

development, including self-regulatory factors, to ultimately improve adolescent weight-

related, dietary, and family mealtime outcomes (Kitzman-Ulrich et al., 2010).

Social Cognitive Theory. Social cognitive theory (SCT) is considered a theory of

reciprocal determinism and asserts that personal, environmental, and behavioral factors

reciprocally interact to determine behavior engagement (Bandura, 1986). SCT considers

self-efficacy to be an essential and flexible determinant for health behaviors (Bandura,

1977; Bandura, 1998). The SCT notes that self-efficacy is a critical prerequisite for

behavior participation, where an individual that believes they are capable of performing a

behavior is more likely to engage in that behavior over time. Self-efficacy is closely

related to self-regulation, a known predictor of adolescent BMI and diet (Francis &

Susman, 2009; Seeyave et al., 2009; Tsukayama et al., 2008). Specifically, perceived

self-efficacy is one determinant of self-regulatory behaviors. For instance, adolescents’

who have greater self-efficacy for eating nutritiously are more likely to engage in

behaviors such as goal-setting, planning, problem-solving, and self-monitoring for their

diet (Bandura, 2004). Overall, both self-efficacy and self-regulation are mechanisms

related to an adolescent’s ability to control their environment and behavior.

The SCT details the importance of self-efficacy development in children, as it

relates to numerous specific health outcomes. In addition to successful mastery the

behavior, self-efficacy can be increased through environmental factors. Literature shows

that parenting styles and practices are known contributors to self-efficacy development in

children. Given the nature of developmental experiences, self-efficacy is largely

considered a construct that can change over time given the presentation of various

situational factors (Bandura, 1997). For instance, authoritative parenting style and

practices have been associated with long-term benefits for adolescent’s self-efficacy

(Schunk & Pajares, 2002). Authoritative parents provide an autonomy-supportive

environment that allows adolescents to build their self-efficacy through mastery

experiences and opportunities (Keshavarz & Mounts, 2017). More so, these parents

typically provide emotional support and encouragement that also serve to improve

adolescents’ self-efficacy. In presenting this environment, authoritative parenting style

and responsive practices may increase adolescent’s self-efficacy. For instance, parental

responsiveness during family meals may create an ideal environment for fostering dietary

self-efficacy. In doing so, authoritative parents help their adolescents develop critical

self-regulation and consequently increase desired behaviors including positive health

behaviors related weight management and diet (Jackson, L.M., Pratt, Hunsberger, &

Pancer, 2005).

Parents may also affect relationships between adolescents’ self-efficacy and BMI

and diet. The SCT highlights the environmental influence on self-efficacy, suggesting

home environment itself may be an important determinant of behavior engagement. This

study aims to assess how changes in adolescent self-efficacy relate to changes in BMI,

diet, and family mealtime over time. The social cognitive theory provides a foundation

for predicting this relationship, where positive changes in self-efficacy will be associated

with positive changes in health outcomes such as BMI and dietary factors, as well as

increases in the quantity and quality of family mealtime. More so, the home environment

that parents create through their parenting styles and behaviors may interact with

adolescent self-efficacy to create stronger, more positive associations with adolescent

BMI, diet, and family mealtime. The proposed study aims to investigate the modifying

role of parenting factors on adolescent self-efficacy in predicting BMI, diet, and family

mealtime. Given the foundations of the social cognitive theory and parents’ ability to

shape adolescent self-efficacy through self-regulatory support and offering mastery

experiences, warm and responsive parenting may interact with adolescent self-efficacy to

predict more positive health outcomes related to BMI, diet, and family mealtime.

Alternatively, demanding and unsupportive parenting may interact with adolescent self-

efficacy to worsen a negative relationship with adolescent BMI, diet, and family

mealtime.

1.2 Prior Literature on Self-Efficacy, Adolescent BMI, Diet, and Family Mealtime

A considerable amount of research has investigated the direct relationships

between adolescent dietary self-efficacy and BMI and dietary outcomes. However, much

of this literature is cross-sectional and does not investigate these relationships over time.

The following sections review current literature that examines associations between

adolescent self-efficacy and BMI, fruit and vegetable intake, fat intake, kcal intake, and

family mealtime.

BMI. Recent research has shown that greater adolescent self-efficacy is related to

adolescent BMI. Some of these studies have investigated the association in the context of

weight-related interventions. For instance, Lee and colleagues (2020) recently examined

the effects of a nutrition-based intervention on obese adolescents’ dietary self-efficacy

and BMI (Lee et al., 2020). The researchers found that over the course of the program,

changes in adolescent dietary self-efficacy were significantly associated with changes in

BMI for adolescents in the intervention (dietary education) group, such that increases in

self-efficacy related to decreases in BMI (n = 168, average 10.95 years, Korean sample).

This finding not only highlights the relationship between adolescent self-efficacy and

BMI, but also emphasizes direct influence of self-regulation on weight-status over time.

Similarly, Miri and colleagues (2019) studied the effects of a randomized controlled trial

aimed to improve nutrition in adolescents with overweight and obesity (n = 55;13 – 18

years). The results of the study indicated that greater adolescent self-efficacy was related

to decreases in BMI (Miri et al., 2019). Results of this study signify the benefits of

interventions aimed to increase aspects of self-regulation among overweight adolescents.

Specifically, this recent study demonstrates that self-regulatory factors are a meaningful

point of intervention for adolescents with overweight and obesity. Another recent study

assessed the effects of an obesity prevention study for families (Herget et al., 2015).

Herget and colleagues (2015) found that over the course of study, adolescents’ self-

efficacy was not significantly related to changes in BMI (n = 157, 10-17 years).

However, general self-efficacy may not directly map onto dietary self-efficacy and this

distinction may have contributed to the null finding.

Though longitudinal research is limited, numerous cross-sectional studies have

highlighted the significant associations between adolescent self-efficacy and BMI.

Results of these studies have primarily supported an inverse relationship between these

two variables, where greater self-efficacy is related to healthier BMI and lower self-

efficacy is related to higher BMI (Fu et al., 2020; Gamble et al., 2009; Miri et al., 2017;

O’Dea & Wilson, 2006; Steele et al., 2011b; Woltering et al., 2021). Some of these

studies have drawn direct comparisons between normal weight and overweight/obese

adolescents. Specifically, when grouped separately, overweight and obese adolescents

reported significantly lower weight-related self-efficacy when compared to normal

weight adolescents (Miri et al., 2017; Steele et al., 2011b; Woltering et al., 2021).

However, other studies have found associations in unexpected directions (Brogan et al.,

2012; Williams et al., 2020). Namely, Brogan and colleagues (2012) found that when

normal weight and obese adolescents were compared, there was a positive association

between higher self-efficacy and obesity (Brogan et al., 2012; n = 67, 12 – 17 years,

100% African American). Despite these findings, several recent cross-sectional studies

found no association between adolescent self-efficacy and BMI (Chae et al., 2018; Lloyd-

Richardson et al., 2012; Prioste et al., 2017; Rinderknecht & Smith, 2004; Ward et al.,

2006). These mixed findings support the need for further longitudinal research that

evaluates changes over time in adolescent self-efficacy on predicting BMI and dietary

outcomes.

Diet. Of the health outcomes of interest, the majority of recent research has

focused on investigating the role of adolescent self-efficacy in fruit and vegetable intake

(Bere & Klepp, 2004; Bruening et al., 2010; Cho & Kim, 2018; Franko et al., 2013;

Granner & Evans, 2012; Lotrean & Tutui, 2015; Monge-Rojas et al., 2002; Parks et al.,

2018; Pearson et al., 2011b, 2017; Sato et al., 2020; Trude et al., 2016; Vereecken et al.,

2005; Zabinski et al., 2006). While current literature primarily focuses on cross-sectional

effects, two longitudinal studies have assessed the relationship between adolescent self-

efficacy and fruit and vegetable consumption over time. Bere and Klepp (2005) assessed

a large sample of adolescents (average age at baseline 11.8 years) to determine whether

SCT constructs were related to fruit and vegetable intake. The results of their study not

only indicated correlations between self-efficacy and fruit and vegetable consumption,

but also found that changes in adolescent self-efficacy were significantly related to

changes in fruit and vegetable intake over time (Bere & Klepp, 2005; n = 1950, 10-12

years). In a more recent longitudinal study, Pearson and colleagues (2011) surveyed

Australian adolescents during their 7

year in school and again two years later to

determine predictors for dietary intake (n = 1850, 12 – 15 years). The authors found that

adolescent self-efficacy for increasing fruit predicted increases in fruit consumption and

vegetable consumption approximately one year later (Pearson et al., 2011b). The bulk of

existing cross-sectional literature has also found that adolescent self-efficacy is associated

with fruit and vegetable intake (Bere & Klepp, 2004; Bruening et al., 2010; Cho & Kim,

2018; Granner & Evans, 2012; Lotrean & Tutui, 2015; Parks et al., 2018; Sato et al.,

2020; Trude et al., 2016). Specifically, these studies have found that greater adolescent

dietary self-efficacy is significantly associated with greater fruit and vegetable

consumption. Not all of the relevant studies found consistent results, with some studies

finding no evidence for a relationship between self-efficacy and dietary outcomes and

others demonstrating mixed findings (Cho & Kim, 2018; Franko et al., 2013; Frenn et

al., 2003; Pearson et al., 2017; Vereecken et al., 2005; Zabinski et al., 2006). Overall,

these findings provide support for the positive relationship between adolescent self-

efficacy and desirable health outcomes related to BMI and dietary outcomes. Given this

evidence, the proposed study will contribute to existing literature by assessing how the

changes in adolescent self-efficacy relate to the changes in adolescent dietary intake over

time.

Taken together, these findings highlight the role of adolescent self-efficacy on

BMI and dietary outcomes. Limited longitudinal research demonstrates that adolescent

self-efficacy was predictive of adolescent BMI and dietary intake. This study will add to

existing literature by investigating the associations among longitudinal changes in these

variables with a focus on high risk, overweight African American adolescents.

Family Mealtime. Limited literature exists that demonstrates direct relationships

between adolescent self-efficacy and frequency or quality of family mealtime. In fact,

only one recent study was identified that considered the relationship between self-

efficacy and family mealtime variables. Woodruff and Kirby (2013) assessed cross-

sectional associations between cooking self-efficacy and frequency of family dinners in

youth (Woodruff and Kirby, 2013; n = 145, 9-14 years, 23% minorities). The results

indicated that participants with greater self-efficacy were more likely to have a higher

frequency of family dinners. Interestingly, results also indicated that family attitudes and

behaviors (i.e. familial interactions) were significantly associated with frequency of

family dinners.

Some literature also questions the direction of such associations, noting that the

relationship between adolescent self-efficacy and family mealtime may be reciprocal in

nature (Dallacker et al., 2019). In other words, adolescents with greater self-efficacy may

feel more engaged with family meals due to their positive self-perceptions, and nurturing

family mealtime environments may contribute to improved adolescent self-efficacy.

This study will address a gap in literature by investigating the associations

between adolescent self-efficacy and family mealtime frequency and quality among

African American adolescents.

1.3 Prior Literature on Parenting and Adolescent BMI, Diet, and Family Mealtime

BMI. Research suggests that parenting style is associated with adolescent BMI.

Namely, authoritative parenting as characterized by high responsiveness and appropriate

demandingness has been largely related to healthier adolescent BMIs (Shloim et al.,

2015; Sleddens et al., 2011). This review will focus on research with adolescent samples,

a less represented group in this literature. Few longitudinal studies exist that evaluate the

relationship between parenting style and adolescent BMI over time and results of existing

literature vary (Berge, Wall, Loth, & Neumark-Sztainer, 2010b; Fuemmeler et al., 2012;

Lane, Bluestone, & Burke, 2013). Berge and colleagues (2010) assessed the influence of

maternal parenting style on adolescent BMI over a 5-year follow-up (11-18 years, 18.7%

African American). The results of this study indicated that maternal authoritative

parenting style predicted a lower, healthier BMI in adolescents 5 years later, which may

suggest that it is a protective factor for obesity in adolescents (Berge et al., 2010a).

Similarly, Fuemmeler and colleagues (2012) found that authoritarian parenting style

(characterized by low parental responsiveness) was associated with greater increases in

BMI for adolescents (11-21 years, 17.1% African American). Another longitudinal study

found that maternal authoritarian parenting was predictive of higher adolescent BMI (11-

18 years) in sons (Berge et al., 2010b). Although only few studies exist that examine

these relationships over time, significant evidence exists that links authoritative parenting

style to healthier weight outcomes in adolescents, including African American

adolescents (Loncar et al., 2021b; Shloim et al., 2015b; Sleddens et al., 2011).

Despite the limited longitudinal analyses, other studies have outlined the positive

effects of parenting involvement on adolescents’ weight outcomes (Janicke et al., 2008;

Jelalian et al., 2010, 2015; Mellin et al., 1987; R. G. Steele et al., 2012; West et al.,

2010). For instance, West and colleagues (2010) evaluated the effects of a parent-focused

intervention for weight management in overweight and obese children (West et al.,

2010). The intervention, Group Lifestyle Triple P, aimed to help parents adjust their

parenting approaches around weight-related behaviors (diet, physical activity) to be

warmer and more engaged with their children. The authors found that children whose

parents received the intervention experienced significant decreases in BMI compared to

children in the control group (n=101, 4 – 11 years). The results of this intervention

demonstrate that increases in responsive and responsible parenting may lead to healthier

adolescent diets and healthier BMIs. More so, a recent review assessed existing literature

to determine the effects of family-based interventions on adolescent obesity (Bean et al.,

2020). The authors found that studies that targeted parenting style and practices were

largely associated with adolescent weight loss. Specifically, interventions that aimed to

improve parent-adolescent interactions and increase parental responsiveness through

support behaviors showed significant differences in adolescent weight loss when

compared to the control groups. The proposed study will add to this existing literature by

investigating how the temporal stability of parenting style and determining whether

changes parenting styles relate to changes in adolescent BMI over time.

Parental practices or behaviors have also been associated with adolescent BMI

(Kipp et al., 2021; Loncar et al., 2021). Specifically, a substantial amount of literature

exists that demonstrates the association between parental feeding practices and adolescent

weight-status (Faith et al., 2004; Shloim et al., 2015a) Parental feeding practices are

especially critical, as they may influence dietary self-regulation development in

adolescents (Hennessy, et al., 2010). Further, recent literature has suggested that dietary

self-regulation influences adolescent weight over time (Connell & Francis, 2014). This

study will focus on responsibility and monitoring, two common feeding behaviors

consistent with those measured in the Child Feeding Questionnaire (CFQ; Birch et al.,

2001b). Only one recent study evaluated the role of parental responsibility and

monitoring in adolescent weight status over time (Holland et al., 2014). In their large

family-based intervention aimed to improve child BMI, Holland and colleagues (2014)

determined that increases in parental responsibility were associated with decreases in

child BMI (7-11 years, 17.1% African American). While no effects were found for

parental monitoring, the study results suggest that parents’ perceived role in providing

responsible eating choices was associated with healthier child BMI. Some cross-sectional

studies emphasized the link between parental monitoring and adolescent BMI, primarily

demonstrating that greater parental monitoring was associated with higher adolescent

BMI (Schmidt et al., 2017; Towner et al., 2015). Apart from these findings, remaining

existing literature did not demonstrate relations between parental responsibility and

monitoring and adolescent weight-status (Blissett & Bennett, 2013b; Gray et al., 2010;

Hennessy et al., 2010; Huang et al., 2012; Kaur et al., 2006a). This study will advance

existing literature by providing longitudinal perspectives on these relationships. Namely,

the proposed study will investigate whether changes in parental responsibility and

parental monitoring relate to changes in adolescent health outcomes specific to BMI.

Furthermore, the secondary aim of this study will determine whether these parenting

factors interact with adolescent self-efficacy to predict BMI related health outcomes.

These are both relevant and novel contributions to literature.

Diet. In addition to BMI outcomes, research also highlights the relationship

between parenting factors and adolescent diet. Literature was reviewed that assessed the

relationship between parenting factors (parenting style, parental feeding practices) and

adolescent fruit and vegetable intake, fat intake, and kcal intake. Literature largely

demonstrates the benefits of an authoritative approach to parenting on youth’s diet. Most

of this research is cross-sectional in design, making it difficult to determine causality.

The existing longitudinal research revealed mixed findings, where more supportive,

authoritative parenting was linked to healthier adolescent dietary intake for some studies

while parenting practices were not associated with adolescent intake in others (Dickens &

Ogden, 2014; Moens & Braet, 2007; Pearson et al., 2010a). However, a substantial body

of cross-sectional literature shows that authoritative parenting style and practices are

related to greater fruit and vegetable in adolescents (Franchini et al., 2011; Kremers et al.,

2003; Monge-Rojas et al., 2010; Pearson et al., 2010b; Watts et al., 2017). Though less

common, studies have also demonstrated links between authoritative parenting and

parenting practices and adolescent kcal and fat intake, where warmer, autonomy-

supportive parenting was associated with less kcal and fat consumption (Haugland et al.,

2019; Kim et al., 2008; Pearson et al., 2010b).

Family Mealtime. Research shows that parents also play a large role in family

mealtimes. Namely, family mealtime is an opportunity for parents to engage in several

behaviors that may influence adolescent health. Dallacker and colleagues (2019) recently

conducted a meta-analysis related to family meals. They determined that parental

modeling of healthy eating, providing higher quality food, and creating a positive

atmosphere were all significant components of children’s nutritional health (Dallacker et

al., 2019). Notably, modeling and creating a positive environment are both characteristics

of authoritative parenting. Alternatively, more restrictive parental feeding practices have

been associated with lower frequency of family meals (Wilson et al., 2021). Ardakani and

colleagues (2023) found that authoritative parenting directly related to family meal

frequency in African American families, demonstrating that more authoritative parenting

was associated with more frequent family meals (n = 211, 10-17 years, 100% African

American; Ardakani et al., 2023). In addition, the results of their study also indicated that

parental monitoring and modeling were also related to more frequent family meals.

Further, a recent finding detailed the positive moderating effects of authoritative

parenting (n = 241, 11-16 years, 100% African American; Wilson et al., 2021).

Specifically, authoritative parenting style was found to positive moderate intervention

effects of the Project FIT motivational + family weight loss (M+FWL) to improve

frequency of family mealtimes.

1.4 Prior Literature on Parenting, Adolescent Self-Efficacy, Adolescent BMI, Diet

and Family Mealtime

The present study aims to investigate the potential moderating effect of parenting

factors on the relationship between adolescent self-efficacy and adolescent BMI, dietary,

and family mealtime outcomes. Understanding how parenting factors interact with

adolescent self-efficacy is necessary for drawing informed hypotheses regarding potential

moderating effects in the present study. While significant theoretical and developmental

literature exists that emphasize parents’ role in their adolescent’s self-efficacy

development, very few studies have examined the relationship between parenting factors

and adolescent self-efficacy (Bandura, 1997). Previous studies have demonstrated

positive associations between responsive parenting and adolescent self-efficacy

(Keshavarz & Mounts, 2017; Kim et al., 2016; Tabak & Zawadzka, 2017; Tam et al.,

2012). For instance, a recent study evaluated the role of parent involvement in

adolescents’ weight management and dietary self-efficacy (Kim et al., 2016). Kim and

colleagues (2016) found that adolescents whose parents helped them with weight-related

behaviors such as goal-setting experienced significant increases in dietary self-efficacy.

The results of this intervention show the positive effects that parent responsiveness may

have on adolescent dietary self-efficacy and may have subsequent influence on

adolescent weight-status. Though few studies assess the relationship between adolescent

dietary self-efficacy, parenting, and adolescent BMI, several recent studies have assessed

these relationships with general self-efficacy. For example, Tabak and Zawadzka (2017)

found positive associations between authoritative parenting and adolescent general self-

efficacy in their longitudinal study aimed to assess parenting effects on youth mental

health (n = 355, 13 -18 years). The results of their study indicated that positive parenting,

identified by characteristics such as responsive parenting and consistent expectations,

was associated with greater general self-efficacy in 13-year-old Polish adolescents

(Tabak & Zawadzka, 2017). The authors also found that mothers’ positive parenting

during adolescence was predictive of their adolescent’s self-efficacy in early adulthood.

In their recent cross-sectional study, Keshavarz and Mounts (2017) assessed the cross-

sectional relationship between perceived paternal parenting style and adolescents’ general

self-efficacy in Iranian families (n=382). Results indicated that paternal authoritative

parenting was positively related to adolescent self-efficacy (Keshavarz & Mounts, 2017).

Another cross-sectional study examined similar associations in a sample of older Asian

adolescents and young adults (Tam et al., 2012). Tam and colleagues (2012) found that

adolescents who perceived their parents to be authoritative also had higher general self-

efficacy (n = 120, 16 – 21 years). These studies highlight parent’s influence on key

aspects of self-regulation development through the caregiving actions they engage in and

the environmental conditions they provide (Bradley & Caldwell, 1995; Wilson et al.,

2017). This current study expands on this literature by examining the interaction of

parenting factors and dietary self-efficacy on adolescent dietary and family mealtime

outcomes over time.

Literature shows that parent’s influence is not limited to main effects. The

previously reviewed literature details the association between adolescent self-efficacy

and adolescent BMI, diet, and family mealtime outcomes, signifying that adolescents’

beliefs about their health-related abilities influence their motivation to engage in health

behaviors, thereby influencing adolescent BMI, diet, and mealtime (Bandura, 2004).

Parenting factors influence adolescent BMI, diet, and family mealtime in a similar way,

where parents can increase adolescent self-efficacy to engage in healthful behaviors

through practices parental practices that provide encouragement and support while

helping their adolescent develop independence, autonomy, and mastery experiences

(Darling & Steinberg, 1993; Kitzman-Ulrich et al., 2010; Lawman et al., 2011; Ryan &

Deci, 2000). Schunk and Pajares (2002) highlight parental influence through the home

environment that parents create, specifically noting the positive association between

warm, stimulating environments and adolescent self-efficacy (Schunk & Pajares, 2002).

These assertions are founded in the social cognitive theory, where Bandura states that

parents are critical providers of self-efficacy information and experiences to children

(Bandura, 1997). Taken together, literature suggests that parenting factors may also

indirectly influence adolescent development and health outcomes by moderating

adolescent self-efficacy on BMI, diet, and family mealtime. In other words, parenting

factors such as parenting style and feeding practices may increase the positive association

between self-regulatory factors and BMI and diet in adolescents.

These effects are demonstrated in recent research where Connell and Francis

(2014) analyzed longitudinal data to determine connections between parenting factors,

child self-control, and child BMI (n=778, 4 - 15 years). The authors assessed self-control

when children were age 4 years through a series of delay of gratification tasks, a metric

for self-regulation. Researchers then tested the interaction of parenting style and self-

regulation on children’s BMI trajectories from 4 -15 years (Connell & Francis, 2014b).

The results of this study indicated that authoritative parenting and permissive parenting,

both characterized by high parental responsiveness, were associated with greater self-

regulation and healthier BMI outcomes in boys. These findings suggest that the

relationship between adolescent self-regulatory processes and health outcomes may be a

function of parenting, where responsive parenting interacts with self-regulation to predict

adolescent weight-status. Similarly, Rhee and colleagues (2016) investigated the

relationship between parenting factors and child BMI on families enrolled in a 16-week

family-based behavioral weight control program (n=40, 8 – 12 years). The authors

concluded that warmer, more responsive parenting created a nurturing environment that

supported the child’s weight-related efforts, such as goal setting and self-monitoring, that

subsequently resulted in healthier weight outcomes (Rhee et al., 2016). These findings

emphasize the function of parenting style and behaviors in adolescent self-regulatory

processes and subsequent health outcomes. Namely, the results suggest that greater

parental nurturance can influence aspects of adolescents’ self-regulation, such as

perceived dietary self-efficacy, to ultimately affect adolescent weight-status and dietary

behaviors.

Anderson and colleagues (2016) reviewed recent literature and reported further

apparent connections between parenting factors and subsequent child health. In their

summary, the authors highlighted the effects of parental sensitivity and responsiveness on

child weight (Anderson & Keim, 2016). For instance, the authors reviewed findings from

an earlier study where maternal sensitivity in early childhood was linked to weight-status

in adolescence (Anderson et al., 2012). More so, Anderson and colleagues (2012)

assessed maternal sensitivity at 15, 24, and 36 months through observation and concluded

that mothers who practiced greater sensitivity in these early years increased their child’s

healthy responses to stress and challenges and ultimately predicted healthier weight

during adolescence (n=977, 1 – 15 years). Similar findings were echoed in studies with

younger samples, where higher maternal sensitivity was related to healthier weight later

in adolescence (Rhee et al., 2006; Wendland et al., 2014; Wu et al., 2011). Research has

also summarized the parental influence on adolescent health behaviors. For instance,

Berge (2014) found that greater parental warmth during mealtimes was associated with

healthier weight throughout childhood (n=120, average 9 years, 74% African American).

The results of this study highlight parents’ role in child development and health, where

increased warmth and positive communication potentially affect adolescents’ self-

perceptions and regulatory beliefs and therefore influence dietary behaviors and weight-

related outcomes (J. M. Berge et al., 2014). Despite the younger samples, these results

illustrate the influence of parenting style and practices on the adolescent self-regulatory

processes that influence BMI and diet.

Limited research was identified that assess explicit interactions between parenting

factors (parenting style and parental feeding practices), adolescent self-regulatory factors,

and adolescent health outcomes (BMI and dietary intake). Furthermore, literature

examining the moderating role of parenting on the association between broader

adolescent self-regulation and BMI and diet is nearly nonexistent. However, some

research has demonstrated moderating effects of parenting on the relationship between

other adolescent self-regulatory behaviors and health outcomes. Quattlebaum and

colleagues (2021) investigated the influence of parental feeding practices in the

association between adolescents’ emotional eating (a metric of low self-regulation) and

dietary outcomes (n = 127, 11-16 years, 100% African American). The authors found that

emotional eating was positively associated with fruit and vegetable intake when parents

demonstrated high levels of monitoring, low restriction, and low concerns (Quattlebaum,

Wilson, Sweeney, and Zarrett, 2021 in press). These findings suggest that adolescents

with lower self-regulatory skills have better dietary outcomes when parents practice

fewer overbearing feeding practices. Additionally, Connell and Francis (2014) conducted

one of the only recent investigations that assessed parents’ role in the relationship

between adolescent self-regulation and BMI, finding that authoritative parenting practices

mitigated the harmful effects of poor self-regulation on adolescent BMI over time (n =

778, 4-15 years, 12% African American; Connell & Francis, 2014). Results of this study

draw attention to indirect effects of parenting on adolescent development and emphasize

the need for further research. This study will add to existing literature by examining

whether parenting factors interact with adolescent self-efficacy to predict adolescent

health outcomes including BMI and dietary outcomes.

1.5 Study Purpose and Hypotheses

In all, prior research has clearly demonstrated relationships between parenting

style, parental feeding practices, adolescent self-efficacy for diet, and adolescent health.

Existing literature highlights the role of parenting in adolescent health (BMI and dietary

intake) and the positive relationship between adolescent self-efficacy for diet and dietary

behaviors. However, while cross-sectional research is abundant there is limited

longitudinal research examining these associations. Fewer studies have examined how

parenting factors relate to adolescent dietary self-efficacy, and literature assessing

interactions between adolescent dietary self-efficacy, adolescent BMI and diet, and

parenting factors is rare. The proposed study aims to build on existing literature in several

ways. First, this study aims to explore the temporal stability of parenting factors and

adolescent dietary self-efficacy while assessing longitudinal relationships with adolescent

BMI and diet. Few studies have assessed the stability of parenting factors or adolescent

dietary self-efficacy over time. More so, little research has evaluated associations

between adolescent self-efficacy and fruit and vegetable intake over time, and no known

studies have evaluated these longitudinal associations with adolescent zBMI, fat intake,

or kcal intake as well as family mealtime. More importantly, no known studies have

investigated the potential moderating effect of parenting factors in the relationship

between adolescent self-efficacy for diet and adolescent BMI and diet. Prior literature

demonstrates that parents play a role in adolescent health behaviors and weight-status,

suggesting parenting factors have the potential to strengthen the positive effects of

adolescent self-efficacy on BMI, diet, and family mealtime. Given the limitations in

current literature, this study will explore the relationships between adolescent self-

efficacy, adolescent BMI, diet, family mealtime and parenting using a longitudinal study

design. In considering the known associations between each of the variables, this study

will focus on evaluating potential interaction effects of parenting practices

(responsibility, monitoring, responsiveness, and demandingness) on the relationship

between adolescent self-efficacy for diet and adolescent health outcomes (BMI, fruit and

vegetable intake, fat intake, and kcal intake and family mealtime). Therefore, the specific

aims and hypotheses for this study are:

Aim 1. To examine the temporal stability of parenting factors and adolescent dietary self-

efficacy to determine associations between adolescent self-efficacy and parenting factors

and how they are related to changes in adolescent health outcomes of diet, zBMI, and

family mealtime from baseline to 16 weeks (post-online intervention; Figure 1.1).

Hypothesis 1a. Increases in adolescent self-efficacy will be related to

improvements in adolescent BMI and diet from baseline to 16 weeks, such that

adolescents who increase self-efficacy from baseline to 16 weeks will also have

decreased zBMIs, increased fruit and vegetable consumption, lower fat intake, lower

kilocaloric intake, and greater frequency and quality of family mealtime at 16 weeks.

Hypothesis 1b. Changes in parenting factors (parent responsiveness, monitoring,

and responsibility, demandingness) will be related to changes in adolescent BMI and diet

from baseline to 16 weeks, such that adolescents whose parents became more responsive

and practiced more dietary responsibility will also have decreased zBMIs, dietary intake

(increased fruit and vegetable consumption, decreased fat intake, and decreased

kilocaloric intake), and increased frequency and quality of family mealtime at 16 weeks.

Adolescents whose parents became more demanding and practiced greater monitoring

will also have increased zBMIs, poorer dietary intake (decreased fruit and vegetable

consumption, increased fat intake, and increased kilocaloric intake), and reduced

frequency and quality of family mealtime at 16 weeks.

Aim 2. To examine whether parenting factors (responsiveness, demandingness,

responsibility, monitoring) moderate the relationship between adolescent self-efficacy

and adolescent zBMI, dietary intake, and family mealtime outcomes (Figure 1.1).

Hypothesis 2. Parenting factors will modify the relationship between adolescent

self-efficacy and adolescent zBMI and diet over time, such that increases in warm and

responsive parenting (responsiveness, parental responsibility for adolescent diet) will be

related to a more positive association between self-efficacy and positive health outcomes

over time (healthier zBMI, increased fruit and vegetable consumption, decreased fat and

kcal intake, increased frequency and quality of family mealtime). In contrast, harsh and

demanding parenting (demandingness, parental monitoring of adolescent diet) will be

related to a negative association between self-efficacy and BMI, diet, and frequency and

quality of family mealtime over time.

Adolescent self-

efficacy for health

behaviors

Parenting Factors

(responsiveness,

demandingness,

responsibility,

monitoring)

Adolescent health and

mealtime outcomes

1. zBMI

2. Dietary outcomes

(kilocaloric, fat,

fruit, and vegetable

intake)

3. Family mealtime

(frequency and

quality)

Figure 1.1 Model of expected relationships between adolescent self-efficacy,

adolescent health outcomes, mealtime outcomes, and parenting factors.

CHAPTER TWO

METHODS

2.1 Participants

Data were collected from 241 African American parent-adolescent dyads that

were enrolled in the Families Improving Together (FIT) for Weight Loss randomized

controlled trial (Alia et al., 2015; Wilson et al., 2015; Wilson et al., 2022). Participants

were recruited through culturally-relevant local events, festivals, advertisements or

through collaboration with local pediatric clinics and parks and recreation partners.

Eligible families met the following criteria: 1) having an African American adolescent

between 11-16 years of age, 2) participating adolescent was overweight or obese, as

defined by having a BMI ≥85

percentile for their age and sex, 3) having an in-home

caregiver willing to participate with the adolescent, and 4) having internet access.

Adolescents with medical or psychiatric conditions that would affect their diet or ability

to exercise were excluded from the study. Caregivers and/or adolescents that were

currently enrolled in another weight loss or health program were also excluded. All

participants signed informed consent forms prior to participation and were given

compensation for their participation in FIT.

Participant (n=241) baseline demographics are described in Table 2.1 The

majority of adolescent participants were female (64%) and the average age was 12.83

years old. The average BMI percentile for adolescents was 96.61 (SD=4.25), placing

them on average in the obese BMI range. The average age for parents was 43.19

(SD=8.65). Most caregivers were unmarried and had an annual income between $25,000

- $39,999.

2.2 Study Design

Project FIT evaluated the efficacy of a family-based motivational weight-loss

intervention as compared to a basic health education program for African American

families (Wilson et al, 2015, Wilson et al., 2022). The current study is longitudinal in

design and evaluates baseline, post-group (8 weeks), and post-online data (16 weeks) of

the larger longitudinal FIT trial. While the FIT trial was an intervention, this study

controls for treatment condition and intervention effects will not be assessed. Full

methods and procedures for Project FIT are explained in separate literature (Wilson et al.,

2015; Wilson et al., 2022).

2.3 Procedures

Prior to enrollment, a trained staff member conducted informed consent with

interested participants. After enrolling, participants completed a “welcome visit,” where

they learned how to report dietary intake during dietary recall measurements. At the

beginning of the program, FIT families attended two orientation sessions (run-in). During

this time, the parent-adolescent dyads completed anthropometric measurements (height

and weight), psychosocial surveys, and dietary recall measurements. Weight and height

measures were obtained using a Seca 880 digital scale and a Shorr height board,

respectively. Adolescent BMI was calculated using these measures with Center for

Disease Control (CDC) growth charts (CDC, 2000), then standardized to BMI z-scores

Table 2.1 Descriptive Baseline Data

Note. N=241

Variable

Value

Adolescent Age M(SD)

12.83 (1.75)

Adolescent Sex (Female), N%

64%

Parent Education, N%

Less Than 4 Year College Degree

127 (56.8%)

4 Year College or Professional Degree

100 (42.2%)

Parent BMI M(SD)

37.49 (8.34)

Parent Age M(SD)

43.18 (8.65)

Parent Income

$25,000-$39,999

Parents Married, N(%)

83 (34.4%)

Children in Home, M(SD)

2.05 (1.20)

Adolescent zBMI, M(SD)

2.05 (0.05)

Adolescent BMI Percentile M(SD)

96.61 (4.25)

(zBMI) using the statistical analysis system (SAS) program. Adolescent-report of

perceived parenting style, parental feeding styles, self-efficacy for diet, and family

mealtime were assessed with psychosocial survey measures. Adolescent dietary intake

was measured through dietary recalls performed by a registered dietician. Participants

repeated anthropometric and psychosocial measures at the post-group timepoint (8

weeks) and repeated anthropometric, psychosocial, and dietary recall and family

mealtime measures at the post-online timepoint (16 weeks). Participants were

incentivized for their time at the conclusion of the each timepoint.

2.4 Measures

Demographic Information. Demographic information was self-reported through

either parent or adolescent psychosocial surveys. These measures included parent age,

adolescent sex, parent annual income, and parent education. Parent education was used as

a measure of socioeconomic status and responses ranged from ‘never attended school,’

‘grades 1-8 (elementary),’ ‘grades 9-11,’ ‘grades 12 or GED (high school graduate),’

‘college 1 year to 3 years (some college or technical school), ‘college 4 years or more

(college graduate),’ and ‘graduate training or professional degree.’ Adolescent age and

parent age were measured at the time of consent through parent-report data. Parent BMI

was calculated using parent baseline measurements.

Predictors Variables

Parenting style. Parenting style was measured using six items from an adolescent

self-report measure, the Authoritative Parenting Index (Jackson, Kimiecik, Ford, &

Marsh, 1998). Informed by Baumrind’s parenting styles (authoritative, authoritarian,

permissive, and neglectful; 1977), the API consists of two subscales of responsiveness

and demandingness. Responses are reported using a 5-point Likert scale ranging from

“not at all like them” to “exactly like them.” Sample items include “My parents make me

feel better when I am upset,” and “My parents have rules that I must follow.” This scale

has been validated for diverse samples. The demandingness and responsiveness subscales

were found to be reliable for adolescents (α = 0.77 and 0.85 respectively). Participants in

this study will respond to 3 items for each subscale (responsiveness, demandingness) for

a total of 6 scored items. Previous studies have demonstrated construct validity of these

measure, for example a significant relationship between parenting style and adolescent

weight was reported, where authoritative parenting was associated with healthier weight-

status in adolescents (Shloim et al., 2015).

Adolescent self-efficacy for health behaviors Adolescent self-efficacy for health

behaviors was measured using the Self-Efficacy for Exercise Behaviors Scale (Sallis,

1988). Data was collected for dietary self-efficacy, but this data was not imputed and

unavailable at the time data analysis. However, the self-efficacy for diet and self-efficacy

for physical activity scales demonstrated correlations between 0.57- 0.73 acoss

timepoints. The adapted self-efficacy scale has previously demonstrated predictive

validity to specifically evaluate self-efficacy for healthy eating in African American

adolescents (Wilson et al., 2002). This adolescent self-report measure consists of 10

items that are related to relapse prevention and behavioral skills. Adolescents are asked to

rate how confident they are that they could continue to engage in health behaviors (i.e.

exercise) for at least six months when experiencing specific challenges. Sample items

include “How sure are you that you can stick to your exercise program when your family

is demanding more time from you?” and “How sure are you that you can stick to

exercising even when you have limited amounts of time??” Responses are scored on a 5-

point Likert scale that ranges from ‘1 = I know I cannot’ to ‘5 = I know I can.’

Child feeding questionnaire. The Child Feeding Questionnaire (CFQ; Birch et

al., 2001b) was used to evaluate parental feeding practices and feeding styles. The parent-

report scale consisted of five subscales measuring five dimensions of feeding: parental

responsibility, restriction, concern, monitoring, and pressure-to-eat. Only parental

responsibility and parental monitoring will be assessed in this study. This scale has been

validated for use with adolescents, and each dimension is sufficiently reliable (Kaur et al.,

2006). Goodness of fit analyses indicated that each of the seven dimensions were valid in

the measure (Kaur et al., 2006a). Items in this questionnaire have been modified to reflect

the adolescent’s perspective on their parent’s feeding practices (rather than the parent’s

perspective on their own style). Responses for each dimension are scored on a 5-point

Likert scale.

Responsibility. The responsibility dimension of the CFQ consists of 3 items and

assessed parental feeding responsibility from the adolescent’s perspective. Sample

questions include “When home, how often is my parent responsible for preparing my

meals?” and “How often is my parent responsible for deciding if I have eaten the right

kind of foods?” Responses range from ‘1 = never’ to ‘5 = always.’

Monitoring. The monitoring dimension of the CFQ consists of 3 items that

evaluated parental monitoring of adolescent diet from the adolescent’s perspective.

Sample questions include “How often does my parent keep track of the sweets (candy,

ice cream, pies, pastries) that I eat?” and “How often does my parent keep track of the

high-fat foods that I eat?” Responses range from ‘1 = never’ to ‘5 = always.’

Outcomes Variables

Adolescent zBMI. Adolescent BMI was measured using height, weight, and age

at the time of data collection measurements. Height and weight measurements were taken

at the first group session. Two measurements were taken for both height and weight for

each participant. A third measure was taken if the two height measurements differed by

more than 1 centimeter or the weight measurements differed by more than 0.5 kilogram.

An average height and an average weight were calculated using these measurements. The

CDC growth curves for adolescent BMI was used to assess this measure. Statistical

Analysis Software (SAS) will be used to standardize adolescent BMI (zBMI) for

comparison.

kCal, fat, fruit, and vegetable intake. Adolescent kCal, fat, fruit, and vegetable

intake were collected using three random 24-hour dietary recalls conducted with a

registered dietician, which has been shown to be a valid measure (Thompson & Subar,

2017). It is the standard to conduct three 24-hour dietary recalls to determine dietary

intake in adolescents (Ebbeling et al., 2012; Patrick et al., 2006). The recalls were by

telephone on two weekdays and one weekend day. Adolescents were given instructions

on how to estimate portion sizes during their baseline visit. During the recall, participants

were asked to report the type and quantity of food they had eaten the previous day. Daily

fruit and vegetable intake (with fried fruit and vegetable items removed), energy intake

(kilocalories), and total fat intake (grams) were estimated, and each outcome was

averaged from the completed recalls for the current study. This data was collected at

baseline and post-online (16 weeks) timepoints only. No dietary data was collected at the

post-group (8 weeks) timepoint.

Frequency and quality of family mealtime. This study aimed to assess the

temporal stability of parenting factors and adolescent self-efficacy as they relate to

adolescent health outcomes. Additionally, the study aimed to determine whether

parenting factors moderate the relationship between adolescent self-efficacy and

adolescent health. Originally, the proposal did not include outcomes related to family

mealtime. However, quality of family mealtime and frequency of family mealtime were

added as outcomes after considering established associations between adolescent health

and family mealtime (Hammons and Fiese, 2011). For the frequency of family mealtime

measure, adolescents were asked to report the number of meals they had with their family

during a typical week using a validated scale (Neumark-Sztainer et al., 2010). Response

choices ranged from 1-6: where 1 (never), 2 (1-2 times), 3 (3-4 times), 4 (5-6 times), 5 (7

times), and 6 (more than 7 times). The scale has been used in diverse racial populations

and shown to have construct validity (Neumark-Sztainer et al., 2010). For the quality of

family mealtime measure, adolescents were asked to rate their family meal environment

by indicating how strongly they agreed with statements regarding family meals. The scale

was validated with a diverse population of youth and was found to be reliable (α = 0.73;

Neumark-Sztainer et al., 2010). There were four items on the measure, which included

statements such as “I enjoy eating meals with my family” and “In my family, dinner time

is about more than just getting food, we all talk to each other.” Item responses ranged

from 1-4: 1 (strongly disagree), 2 (somewhat disagree), 3 (somewhat agree), and 4

(strongly agree).

Table 2.2 Predictor Means and Standard Deviations Across Timepoints, M(SD)

Variable

Baseline

(0 weeks)

Post-Online

(8 weeks)

Post-Group

(16 weeks)

3.76 (0.96)

3.71 (1.00)

3.71 (1.02)

Responsiveness

4.38 (1.02)

4.32 (1.26)

4.19 (1.38)

Demandingness

5.20 (0.80)

5.02 (0.86)

4.91 (1.12)

Responsibility

2.85 (0.51)

2.86 (0.53)

2.99 (0.52)

Monitoring

2.82 (0.98)

3.06 (0.97)

3.18 (0.97)

zBMI

2.06 (0.50)

2.06 (0.51)

2.04 (0.55)

kCal intake (grams/day)

1668.29

(479.34)

---

1750.47

(587.23)

Fat intake (grams/day)

64.67 (21.26)

---

65.79 (20.34)

Fruit intake (servings/day)

1.04 (1.02)

---

1.11 (1.10)

Vegetable intake

(servings/day)

1.38 (0.87)

---

1.63 (1.18)

Freq. Family Meals

(meals/week)

3.46 (1.61)

3.44 (1.55)

3.24 (1.52)

Qual. Family Meals

3.26 (0.65)

3.35 (0.61)

3.17 (0.76)

Note: “SE” represents self-efficacy, “Freq. Family Meals” represents frequency of family

meals, and “Qual. Family Meals" represents quality of family meals

2.5 Data Analytic Plan

Multi-Level Model Building. A growth curve analysis approach was used to

allow for the estimation of effects occurring at multiple time points within an individual.

Models were developed with the R statistical software package, version 4.2.2 (The R

Foundation for Statistical Computing, Vienna, Austria), using a stepped approach. Given

the longitudinal study design, random intercepts and random slopes for time were

included in each model, based upon recommendations by Raudenbush & Bryk (2002).

A growth curve analysis was used, and an extensive model building process

occurred initially to determine a baseline model that would be utilized in further model

building. This first model fit procedure involved testing a series of models with

increasing complexity to predict adolescent zBMI (primary outcome). To determine

which model best fit the data, a series of chi-square difference tests were conducted. If

the more complex model did not yield significantly better fit, then the simpler model was

retained as the final model for this phase of model building. First, the unconditional

model (1) which only included a random intercept was run. The next model (2) was

expanded to include time as a fixed effect. The third model (3) was expanded to consider

the random effect of individuals nested within timepoints. The following model (4)

expanded to consider the random effect of individuals nested within groups within

timepoints and did not yield significantly better fit than the previous model, ꭓ

(9) =

<0.01, p=1.00. Therefore, this model was not retained. A final model (5) was assessed to

consider a fixed effect for time and a random effect for groups. This model yielded

significantly better fit than the previous model, ꭓ

(4) = 741.18, p<0.01, and was retained

(Table 2.2). Thus, the model retained as the best fitting model was a linear growth model

that considered a fixed effect for time and random effect for group. This modeling

approach was used for all subsequent analyses and is consistent with the approach used in

prior Project FIT analyses (Wilson et al., 2022).

Analyses. For Aim 1 and 2, the best fitting model (i.e. the model with the fixed

effect for time and random effect for group) was incorporated for a series of model

comparisons that included theory-based predictors. Using a hierarchical approach, a

series of chi-square difference tests compared a covariate only model, the addition of

main effects, and the addition of interaction terms. Covariates included adolescent age,

adolescent sex, parent education, parent BMI, and a main effect for time (0=baseline, 1=8

weeks, 2=16 weeks). Predictor variables included adolescent self-efficacy (hypothesis 1a)

and parenting variables (parental responsiveness, demandingness, responsibility for

adolescent diet, and monitoring of adolescent diet; Hypothesis 1b). All predictor

variables were z-scored. Two-way interactions between the predictors and time were used

to test Aim 1, and three-way interactions between self-efficacy, time, and the parenting

factors were used to test Aim 2. The model testing Aim 1 on adolescent zBMI is:

Adolescent zBMI = β

+ β

AdolescentAge

+ β

AdolescentSex

+ β

ParentEducation

+ β

ParentBMI

+ β

GroupRandomization

OnlineRandomization

+ β

Timeij +

Self-efficacy

+ β

ParentResponsiveness

+ β

ParentDemandingness

+ β

ParentalResponsibility

+ β

ParentalMonitoring

+ β

Self-Efficacy*Time

+ β

ParentResponsiveness*Time

+ β

ParentDemandingness*Time

ParentalResponsibility*Time

+ β

ParentalMonitoring*Time

+ b

+ ε

where adolescent zBMI is predicted for the individual i in the jth treatment group, β

the intercept across all treatment groups, β

– β

are the effects of covariates, β

is the

effect of time, β

8-12

are main effects of self-efficacy and parenting factors, β

13-17

are the

two-way interactions between self-efficacy and parenting factors. The random effect b

allows for intercepts to differ across treatment groups, thus accounting for any non-

independence of the outcome within groups. Aim 1 of the proposed study concerns

evaluating the effects of parenting and adolescent self-efficacy over time, which are

represented by β

13-17

in the above equation. For Aim 2, three-way interactions between

time, self-efficacy, and parenting factors were added to the model. The same modeling

approach was used to predict dietary and mealtime outcomes.

2.6 Preliminary Analyses and Assumptions

All model assumptions and case diagnostics were tested using R statistical software

package, version 4.2.2 (The R Foundation for Statistical Computing, Vienna, Austria).

Tests to assess assumptions for the multilevel regression analyses were tested before

running outcome analyses. To address the assumption of normality, histograms of

Table 2.3 Model Building

Note. Model 1 is the unconditional model, Model 2 includes time as a fixed effect, Model

3 adds the random effect of individuals nested within timepoints, Model 4 adds the

random effect of individuals nested within groups within timepoints, Model 5 includes a

fixed effect for time and a random effect for groups and was the best fitting model.

Model

logLikelihood

Test

Likelihood Ratio

P-value

-211.89

-211.42

1 vs 2

0.93

0.33

-175.33

2 vs 3

72.18

<0.01

-175.33

3 vs 4

0.00

1.00

-545.92

3 vs 5

741.18

<0.01

the standardized residuals were assessed, and data was found to be normally distributed.

Scatterplots of the standardized residuals and predicted values were evaluated, and

independent variables exhibited homoscedasticity. Additionally, scatterplots were used to

examine variability between groups and confirmed that error is randomly distributed

across levels of each model predictor. A Durbin-Watson test was used to assess

independence of errors. A Cook’s distance measure was used to check for influential

points in the data and no cases were deemed to be significantly influential so final models

include all 241 participants. Bivariate correlations between independent variables were

used to assess potential multicollinearity. Effect sizes were in appropriate ranges,

indicating this assumption was not violated.

Adolescent zBMI was measured over time (baseline and post-intervention) and

longitudinal assumptions including stability, stationarity, and equilibrium was tested.

Stability of the mean over time was examined by comparing means of zBMI at both time

points. Stationarity, which assumes that zBMI measurements were obtained in the same

manner at baseline and post-intervention, has been met due to the strict protocol for

obtaining BMI measurements by trained staff during the intervention. Equilibrium, which

assumes temporal stability in the patterns of covariance and variance among variables,

was tested by comparing variance and covariance scores across the two measurements of

zBMI. These preliminary analyses demonstrated that multilevel modeling assumptions

were met.

2.7 Missing Data

Missing data in the larger FIT trial was assumed to be missing at random. BMI

data were missing for 0.8% of adolescents at baseline and 14.5% of adolescents at 16

weeks. Dietary data were included if the participant had at least one dietary recall at each

timepoint. No dietary data was collected at the post-group (8 weeks) timepoint. Dietary

data was averaged for participants with 2-3 dietary recall sessions for each timepoint.

Multiple imputations were used to address missing data using the MICE package in R.

All primary and secondary outcomes, demographic data, and variables of theoretical

importance, including the key variables assessed in the present analyses, were included in

the imputation to minimize the likelihood of biased estimates and meet missing at

random assumptions. A total of 20 datasets were imputed and one random imputation

will be selected for the analyses of the proposed study (Wilson et al., 2021).

CHAPTER THREE

RESULTS

3.1 Correlation Analyses

To assess for multicollinearity, bivariate correlations among model variables were

calculated with alpha set at 0.05 for a two-tailed significance test (Table 3.1). Results

indicated that several covariate, predictor, and outcome variables were correlated across

the three timepoints. Among baseline variables, the strongest positive correlations

included adolescent kCal intake with adolescent fat intake (r = .88), parental

demandingness with parental responsiveness (r = .48), and parental monitoring with

parental responsibility (r = .53). Among post-group variables, the strongest positive

correlations were parental demandingness with parental responsiveness (r = .46) and

parental responsiveness with frequency of family meals (r = .44). The strongest positive

correlations among post-online variables included parental responsiveness and parental

demandingness (r = .42), parental responsiveness and frequency of family meals (r =

.40), and adolescent kCal intake and fat intake (r = .81). Across timepoints, the strongest

correlations included baseline and post-group adolescent self-efficacy (r = .46), baseline

and post-group responsiveness (r = .52), baseline zBMI with post-group zBMI (r = .84)

and post-online zBMI (r = .79), post-group and post-online zBMI (r = .93), and post-

group with post-online demandingness (r = .44).Though kCal intake and fat were highly

correlated, they were not included in the same model and therefore did not violate the

multicollinearity assumption. The effect sizes for other correlations fell within the small-

to-medium range, indicating that the assumption for multicollinearity was not violated.

3.2 Primary Outcome zBMI. For the zBMI outcome, the addition of the two-way

interaction terms significantly improved the model above the model with main effects

only (Table 3.2). The addition of three-interaction terms did not improve the model, ꭓ

(28) = 7.15, p=0.52), but the three-way interaction terms were retained to interpret Aim 2.

Addressing Aim 1, results from the final model indicated a significant two-way

interaction between parental responsibility and time, Estimate=0.09, SE = 0.02, p<0.01.

Unexpectedly, zBMI decreased across timepoints for adolescents whose parents had low

responsibility for their diet, and zBMI increased across time for adolescents whose

parents had high responsibility for their diet (Figure 3.1) The unexpected outcomes are

considered in the discussion section.

Results also indicated a significant two-way interaction between parental

monitoring and time, Estimate=-0.10, SE = 0.02, p<0.01. The plot of the interaction

demonstrated that zBMI decreased over time for adolescents whose parents had high

levels of monitoring for their diet, and zBMI increased over time for adolescents whose

parents had low levels of monitoring (Figure 3.2). These findings were inconsistent with

the hypothesized relationship between parental monitoring and adolescent zBMI and are

considered further in the discussion.

There was no significant two-way interaction between self-efficacy and time

(Hypothesis 1a), or time and any other parenting factors (Hypothesis 1b), and no

significant three-way interactions (Hypothesis 2).

Table 3.1 Correlations between predictors and outcome variables

Note. Covariates (adolescent age, adolescent sex, parent education, parent BMI) not included. [0], baseline; [1], post-group;

[2], post-only.

Table 3.2 Hierarchical Approach for zBMI

Note. Model 1 included covariates and time; Model 2 included covariates, time, predictor

variables (parenting variables and self-efficacy); Model 3 included covariates, time,

predictor variables, and interactions with time; Model 4 included covariates, time,

predictor variables, interactions with time, and three-way interactions with adolescent

self-efficacy, parenting variables, and time.

Table 3.3: Outcome Analyses - zBMI

Note: “SE” represents self-efficacy.

Estimate

T-value

P-value

Lower

95% CI

Upper

95% CI

Intercept

2.00

0.06

31.92

0.00

1.88

2.12

Group Randomization

0.07

0.05

1.50

0.14

-0.02

0.16

Online Randomization

0.04

1.19

0.24

-0.03

0.11

Child Age

-0.04

0.01

-3.62

<0.01

-0.06

-0.02

Child Sex

0.00

0.04

0.14

0.89

-0.07

0.08

Parent Education

0.06

0.04

1.54

0.12

-0.01

0.13

Parent BMI

0.02

0.00

10.24

<0.01*

0.02

0.03

-0.05

0.05

-1.03

0.31

-0.14

0.04

Time

-0.02

0.02

-0.86

0.38

-0.06

0.02

Responsiveness

-0.04

0.05

-0.79

0.43

-0.15

0.06

Demandingness

-0.04

0.05

-0.71

0.48

-0.14

0.07

Responsibility

-0.15

0.05

-2.75

<0.01*

-0.26

-0.05

Monitoring

0.22

0.05

4.01

<0.01*

0.11

0.32

SE*Time

0.01

0.02

0.63

0.53

-0.03

0.06

SE*Responsiveness

0.00

0.05

0.18

0.86

-0.09

0.11

Time*Responsiveness

-0.00

0.02

-0.04

0.96

-0.05

0.05

SE*Demandingness

0.00

0.06

0.01

0.99

-0.11

0.11

Time*Demandingness

0.01

0.02

0.49

0.63

-0.03

0.06

SE*Responsible

-0.01

0.06

-0.15

0.88

-0.12

0.10

Time*Responsible

0.09

0.02

3.65

<0.01*

0.04

0.14

SE*Monitor

-0.06

0.05

-1.09

0.28

-0.16

0.05

Time*Monitor

-0.10

0.02

-4.30

<0.01*

-0.15

-0.06

SE*Time*Responsiveness

-0.00

0.02

-0.17

0.86

-0.05

0.04

SE*Time*Demandingness

0.00

0.02

0.14

0.89

-0.04

0.05

SE*Time*Responsible

-0.00

0.02

-0.15

0.89

-0.05

0.04

SE*Time*Monitor

0.04

0.02

1.76

0.08

0.00

0.08

Model

logLikelihood

Test

Likelihood Ratio

P-value

-487.67

-482.07

1 vs 2

11.20

<0.05

-470.32

2 vs 3

23.512

<0.01

-466.74

3 vs 4

7.15

0.52

Figure 3.1 Interaction between parental responsibility and time in predicting adolescent

zBMI.

Figure 3.2 Interaction between parental monitoring and time in predicting adolescent

zBMI.

3.3 Secondary Outcome kCal Intake. Model comparisons were completed using the

same methods as the zBMI model and a total of three chi-square comparisons were

completed (Table 3.4). For the kCal outcome, the best-fitting model was Model 4, which

included three-way interactions (ꭓ

(28) = 15.72, p<0.05). Results indicated a significant

three-way interaction between adolescent self-efficacy, time, and parental

demandingness, Estimate=62.83, SE = 28.13, p<0.05 (Table 3.5). As shown in Figure

3.4, self-efficacy was associated with greater kCals among those with low

demandingness and lower kCals among those with high demandingness at baseline.

However, this interaction attenuated across time. This finding is inconsistent with the

hypothesis that greater parental demandingness would be associated with higher

adolescent kCal intake across timepoints. There were no other significant three-way

interactions (Hypothesis 2), nor significant two-way interactions (Hypothesis 1a and 1b).

However, a significant main effect existed for parental responsiveness, Estimate=127.37,

SE = 63.65, p<0.05, indicating that parental responsiveness was associated with greater

adolescent kCal intake, and remained stable over time.

3.4 Secondary Outcome Fat Intake. Model comparisons for adolescent fat intake were

completed using the same methods as the other models and a total of three chi-square

comparisons were completed (Table 3.6). For the fat outcome, the best-fitting model was

Model 4, which included three-way interactions (ꭓ

(28) = 16.58, p<0.05).

Similar to the kCal model, results indicated a significant three-way interaction

between adolescent self-efficacy, time, and parental demandingness, Estimate=3.09, SE =

1.09, p<0.01 (Table 3.7) As shown in Figure 3.4, self-efficacy was associated with

greater fat intake among

Table 3.4 Hierarchical Approach for kCal intake

Note. Model 1 included covariates and time; Model 2 included covariates, time, predictor

variables (parenting variables and self-efficacy); Model 3 included covariates, time,

predictor variables, and interactions with time; Model 4 included covariates, time,

predictor variables, interactions with time, and three-way interactions with adolescent

self-efficacy, parenting variables, and time.

Table 3.5 Model Outcome Analysis - kCal intake

Note: “SE” represents self-efficacy.

Model

logLikelihood

Test

Likelihood Ratio

P-value

-3697.91

-3693.93

1 vs 2

7.97

0.15

-3692.02

2 vs 3

3.82

0.58

-3684.16

3 vs 4

15.72

<0.05

Estimate

T-

value

P-

value

Lower

95% CI

Upper

95% CI

Intercept

1511.06

75.37

20.05

0.00

1366.95

1655.16

Group Randomization

52.10

58.23

0.89

0.38

-62.13

166.32

Online Randomization

63.16

47.81

1.32

0.19

-28.26

154.57

Child Age

18.99

14.25

1.33

0.18

-8.25

46.23

Child Sex

207.65

51.60

4.02

<0.01*

108.99

306.30

Parent Education

-34.67

50.68

-0.68

0.49

-131.56

62.22

Parent BMI

-3.12

2.85

-1.09

0.27

-8.58

2.33

45.37

55.45

0.82

0.41

-60.65

151.40

Time

38.57

24.63

1.57

0.12

-8.52

85.66

Responsiveness

127.37

63.65

2.00

<0.05*

5.69

249.06

Demandingness

-0.03

63.98

0.00

1.00

-122.35

122.29

Responsibility

-35.34

65.01

-0.54

0.59

-159.64

88.97

Monitoring

-67.46

64.17

-1.05

0.29

-190.15

55.24

SE*Time

-27.43

24.38

-1.12

0.26

-74.04

19.19

SE*Responsiveness

-4.24

64.18

-0.07

0.95

-126.96

118.47

Time*Responsiveness

-30.00

27.40

-1.09

0.27

-82.39

22.39

SE*Demandingness

-113.45

71.18

-1.59

0.11

-249.53

22.64

Time*Demandingness

-13.89

26.93

-0.52

0.61

-65.38

37.60

SE*Responsible

12.31

68.12

0.18

0.86

-117.93

142.54

Time*Responsible

3.05

27.24

0.11

0.91

-49.03

55.12

SE*Monitor

54.49

64.85

0.84

0.40

-69.49

178.47

Time*Monitor

23.82

26.56

0.90

0.37

-26.95

74.60

SE*Time*Responsiveness

-9.96

26.07

-0.38

0.70

-59.81

39.89

SE*Time*Demandingness

62.83

28.13

2.23

0.03*

9.05

116.62

SE*Time*Responsible

-4.59

26.72

-0.17

0.86

-55.68

46.49

SE*Time*Monitor

-45.91

26.10

-1.76

0.08

-95.82

4.00

Figure 3.3 Interaction between adolescent self-efficacy and parental demandingness on

adolescent kCal intake at baseline, 8 weeks, and 16 weeks.

Table 3.6 Hierarchical Approach for fat intake

Note. Model 1 included covariates and time; Model 2 included covariates, time, predictor

variables (parenting variables and self-efficacy); Model 3 included covariates, time,

predictor variables, and interactions with time; Model 4 included covariates, time,

predictor variables, interactions with time, and three-way interactions with adolescent

self-efficacy, parenting variables, and time.

Table 3.7 Model Outcome Analysis - Fat

Note: “SE” represents self-efficacy.

Model

logLikelihood

Test

Likelihood Ratio

P-value

-2133.52

-2129.16

1 vs 2

8.72

0.12

-2125.01

2 vs 3

8.30

0.14

-2116.72

3 vs 4

16.58

0.03

Estimate

T-value

P-value

Lower

95% CI

Upper

95%

Intercept

59.33

2.95

20.13

0.00

53.69

64.96

Group Randomization

3.51

2.34

1.50

0.14

1.09

8.11

Online Randomization

3.41

1.84

1.85

0.07

-0.12

6.94

Child Age

0.32

0.55

0.57

-0.74

1.37

Child Sex

5.68

2.00

2.85

<0.01*

1.87

9.50

Parent Education

-0.67

1.96

-0.34

0.73

-4.42

3.08

Parent BMI

-0.11

0.11

-1.06

0.29

-0.33

0.09

1.23

2.14

0.58

0.56

-2.86

5.34

Time

1.19

0.95

0.20

0.84

-1.63

2.00

Responsiveness

6.15

2.46

2.50

0.01*

1.44

10.85

Demandingness

1.06

2.47

0.43

0.67

-3.67

5.78

Responsibility

-1.59

2.51

-0.63

0.53

-6.39

3.21

Monitoring

-2.07

2.48

-0.84

0.40

-6.82

2.67

SE*Time

-0.79

0.94

-0.84

0.40

-2.59

1.01

SE*Responsiveness

0.90

2.48

0.36

0.72

-3.84

5.64

Time*Responsiveness

-1.85

1.06

-1.75

0.08

-3.88

0.17

SE*Demandingness

-6.95

2.75

-2.53

0.01*

-12.20

-1.69

Time*Demandingness

-0.99

1.04

-0.96

0.34

-2.98

0.99

SE*Responsible

0.09

2.63

0.04

0.97

-4.94

5.13

Time*Responsible

-0.03

1.05

-0.03

0.98

-2.04

1.98

SE*Monitor

1.93

2.51

0.77

0.44

-2.86

6.72

Time*Monitor

0.56

1.03

0.54

0.59

-1.40

2.52

SE*Time*Responsiveness

-1.03

1.01

-1.02

0.31

-2.96

0.89

SE*Time*Demandingness

3.09

1.09

2.85

<0.01*

1.02

5.17

SE*Time*Responsible

0.13

1.03

0.12

0.90

-1.85

2.10

SE*Time*Monitor

-1.45

1.01

-1.43

0.15

-3.37

0.48

Figure 3.4 Interaction between adolescent self-efficacy and parental demandingness on

adolescent fat intake at baseline, 8 weeks, and 16 weeks.

those with low demandingness and lower fat intake among those with high

demandingness at baseline. However, this interaction also attenuated across time. This

finding is inconsistent with the hypothesized direction of the relationship between

adolescent fat intake, self-efficacy, and parental demandingness. There were no other

significant three-ways interactions (Hypothesis 2), nor any two-way interactions

(Hypothesis 1a, 1b). However, a significant main effect existed for parental

responsiveness, Coefficient=6.15, SE = 2.46, p<0.01, indicating that greater parental

responsiveness was associated with greater adolescent fat intake, and was stable across

time. This finding is considered further in the discussion section.

3.5 Secondary Outcome Fruit Intake. Model comparisons for adolescent fruit intake

were completed using the same methods as the other models and a total of three chi-

square comparisons were completed (Table 3.8). No models were a significantly better fit

than Model 1 (covariates only model). However, for the fruit outcome, the best-fitting

model was considered to be Model 2, which included only main effects (ꭓ

(15) = 10.03,

p=0.07). However, all interaction terms remained in the final model for interpretation.

There was no significant two-way interaction between self-efficacy and time (Hypothesis

1a), or time and any parenting factors (Hypothesis 1b), and no three-way interactions

(Hypothesis 2; see Table 3.9).

3.6 Secondary Outcome Vegetable Intake. Model comparisons for adolescent

vegetable intake were completed using the same methods as the other models and a total

of three chi-square comparisons were completed (Table 3.10). For the vegetable outcome,

the best-fitting model was Model 3, which included the two-way interaction terms, as the

last model (which included three-way interactions; ꭓ

(28) = 4.63, p=0.80) did not fit the

Table 3.8 Hierarchical Approach for fruit intake

Note. Model 1 included covariates and time; Model 2 included covariates, time, predictor

variables (parenting variables and self-efficacy); Model 3 included covariates, time,

predictor variables, and interactions with time; Model 4 included covariates, time,

predictor variables, interactions with time, and three-way interactions with adolescent

self-efficacy, parenting variables, and time.

Table 3.9 Model outcome analysis – fruit intake

Note: “SE” represents self-efficacy.

Model

logLikelihood

Test

Likelihood Ratio

P-value

-706.61

-701.59

1 vs 2

10.03

0.07

-698.92

2 vs 3

5.34

0.38

-696.56

3 vs 4

4.72

0.79

Estimate

T-value

P-value

Lower

95%

Upper

95%

Intercept

1.04

0.15

7.04

0.00

0.76

1.32

Group Randomization

-0.09

0.10

-0.92

0.36

-0.29

0.10

Online Randomization

0.10

0.97

0.33

-0.09

0.28

Child Age

0.00

0.03

0.12

0.89

-0.05

0.06

Child Sex

-0.06

0.11

-0.54

0.59

-0.26

0.14

Parent Education

-0.03

0.10

-0.25

0.80

-0.22

0.17

Parent BMI

0.01

0.00

1.76

0.08

0.00

0.02

0.09

0.11

0.82

0.41

-0.12

0.31

Time

0.02

0.05

0.45

0.65

-0.07

0.12

Responsiveness

0.17

0.13

1.32

0.19

-0.08

0.42

Demandingness

-0.12

0.13

-0.95

0.34

-0.37

0.13

Responsibility

-0.07

0.13

-0.50

0.61

-0.32

0.19

Monitoring

0.18

0.13

1.39

0.17

-0.07

0.43

SE*Time

-0.06

0.05

-1.16

0.25

-0.15

0.04

SE*Responsiveness

0.14

0.13

1.07

0.29

-0.11

0.39

Time*Responsiveness

-0.05

0.05

-0.87

0.38

-0.16

0.06

SE*Demandingness

-0.12

0.14

-0.85

0.39

-0.40

0.15

Time*Demandingness

-0.01

0.06

-0.23

0.82

-0.12

0.09

SE*Responsible

0.02

0.14

0.13

0.90

-0.25

0.28

Time*Responsible

0.00

0.06

0.10

0.92

-0.10

0.11

SE*Monitor

0.04

0.13

0.27

0.79

-0.22

0.29

Time*Monitor

-0.05

0.05

-0.84

0.40

-0.15

0.06

SE*Time*Responsiveness

-0.06

0.05

-1.21

0.23

-0.17

0.04

SE*Time*Demandingness

0.07

0.06

1.15

0.25

-0.04

0.18

SE*Time*Responsible

0.00

0.05

0.00

1.00

-0.10

0.10

SE*Time*Monitor

0.04

0.05

-0.72

0.47

-0.14

0.06

Table 3.10 Hierarchical Approach for vegetable intake

Note. Model 1 included covariates and time; Model 2 included covariates, time, predictor

variables (parenting variables and self-efficacy); Model 3 included covariates, time,

predictor variables, and interactions with time; Model 4 included covariates, time,

predictor variables, interactions with time, and three-way interactions with adolescent

self-efficacy, parenting variables, and time.

Table 3.11 Model outcome analysis – vegetable intake

Note: “SE” represents self-efficacy.

Model

logLikelihood

Test

Likelihood Ratio

P-value

-698.40

-696.40

1 vs 2

3.99

0.55

-691.95

2 vs 3

8.91

0.11

-689.64

3 vs 4

4.63

0.80

Estimate

T-value

P-value

Lower

95%

Upper

95%

Intercept

1.18

0.15

8.10

0.00

0.90

1.46

Group Randomization

0.12

0.10

1.21

0.23

-0.07

0.31

Online Randomization

0.16

0.10

1.68

0.09

-0.02

0.35

Child Age

-0.01

0.03

-0.23

0.81

-0.06

0.05

Child Sex

-0.17

0.10

-1.60

0.11

-0.36

0.03

Parent Education

0.02

0.10

0.18

0.86

-0.17

0.21

Parent BMI

0.00

0.01

-0.70

0.49

-0.01

0.01

-0.10

0.11

-0.90

0.37

-0.31

0.11

Time

0.11

0.05

2.15

0.03

0.01

0.20

Responsiveness

0.11

0.13

0.83

0.41

-0.14

0.35

Demandingness

-0.14

0.13

-1.05

0.29

-0.38

0.11

Responsibility

0.08

0.13

0.64

0.52

-0.17

0.33

Monitoring

0.18

0.13

1.40

0.16

-0.07

0.43

SE*Time

0.07

0.05

1.33

0.18

-0.03

0.16

SE*Responsiveness

0.08

0.13

0.58

0.56

-0.17

0.32

Time*Responsiveness

0.00

0.06

-0.04

0.97

-0.11

0.10

SE*Demandingness

0.10

0.14

0.70

0.48

-0.17

0.37

Time*Demandingness

0.03

0.05

0.50

0.62

-0.08

0.13

SE*Responsible

-0.16

0.14

-1.15

0.25

-0.42

0.10

Time*Responsible

-0.07

0.06

-1.31

0.19

-0.18

0.03

SE*Monitor

0.06

0.13

0.49

0.62

-0.19

0.31

Time*Monitor

-0.09

0.05

-1.71

0.09

-0.19

0.01

SE*Time*Responsiveness

-0.02

0.05

-0.41

0.68

-0.12

0.08

SE*Time*Demandingness

-0.06

0.06

-1.10

0.27

-0.17

0.05

SE*Time*Responsible

0.08

0.05

1.43

0.15

-0.03

0.18

SE*Time*Monitor

-0.02

0.05

-0.36

0.72

-0.12

0.08

data better. However, the full model, including three-way interactions, was included in

the final model. There was no significant two-way interaction between self-efficacy and

time (Hypothesis 1a), or time and any parenting factors (Hypothesis 1b), and no three-

way interactions (Hypothesis 2; see Table 3.11). Similar to the fruit outcome, this finding

indicates that neither parenting factors nor adolescent self-efficacy interacted with time to

predict adolescent vegetable intake. Additionally, self-efficacy did not interact with

parenting factors to predict adolescent vegetable intake, nor did any variables

independently predict vegetable intake.

3.7 Secondary Outcome Frequency of Family Mealtime. Model comparisons for

frequency of family mealtime were completed using the same methods as the other

models and a total of three chi-square comparisons were completed (Table 3.12). For the

frequency of family mealtime outcome, the best-fitting model was Model 2 (main effects

only; ꭓ

(15) = 188.52, p<0.01). In other words, model fit was not improved with the

addition of two-way interactions (ꭓ

(20) = 7.05, p=0.22) or three-way interactions (ꭓ

(28) = 12.62, p=0.13). However, two-way and three-way interactions are included in the

final model, and all significant effects were interpreted.

Results indicated a significant three-way interaction between adolescent self-

efficacy, time, and parental responsibility, Estimate=0.12, SE =0.04, p<0.01 (Table 3.13).

As shown in Figure 3.5, low self-efficacy was associated with more frequent family

meals among those with highly responsible parents in earlier timepoints (0- and 8-

weeks). High self-efficacy was associated with more frequent family meals among those

with highly responsible parents at 16-weeks. The moderated effects of parental

responsibility increased over 16 weeks (Figure 3.5). There was no significant two-way

Table 3.12 Hierarchical Approach for frequency of family mealtime

Note. Model 1 included covariates and time; Model 2 included covariates, time, predictor

variables (parenting variables and self-efficacy); Model 3 included covariates, time,

predictor variables, and interactions with time; Model 4 included covariates, time,

predictor variables, interactions with time, and three-way interactions with adolescent

self-efficacy, parenting variables, and time.

Table 3.13 Model outcome analysis – frequency of family mealtime

Note: “SE” represents self-efficacy.

Model

logLikelihood

Test

Likelihood Ratio

P-value

-1021.32

-927.06

1 vs 2

188.52

<0.01

-923.54

2 vs 3

7.04

0.22

-917.23

3 vs 4

12.62

0.13

Estimate

T-

value

P-value

Lower

95%

Upper

95%

Intercept

-0.14

0.11

-1.26

0.21

-0.36

0.07

Group Randomization

0.00

0.07

-0.01

0.99

-0.15

0.14

Online Randomization

0.07

0.99

0.32

-0.06

0.19

Child Age

-0.01

0.02

-0.75

0.45

-0.05

0.02

Child Sex

0.07

1.05

0.30

-0.06

0.21

Parent Education

0.27

0.07

3.95

<0.01*

0.14

0.41

Parent BMI

0.00

0.88

0.38

0.00

0.01

0.06

0.09

0.69

0.49

-0.11

0.23

Time

-0.03

0.04

-0.76

0.45

-0.11

0.05

Responsiveness

0.43

0.10

4.23

<0.01*

0.24

0.63

Demandingness

-0.04

0.10

-0.43

0.66

-0.24

0.15

Responsibility

0.23

0.10

2.25

0.02

0.03

0.43

Monitoring

-0.02

0.10

-0.19

0.85

-0.21

0.18

SE*Time

0.02

0.04

0.45

0.65

-0.06

0.10

SE*Responsiveness

0.17

0.10

1.66

0.10

-0.03

0.36

Time*Responsiveness

-0.06

0.05

-1.24

0.22

-0.15

0.03

SE*Demandingness

0.12

0.11

-1.13

0.26

-0.33

0.09

Time*Demandingness

0.05

1.21

0.23

-0.03

0.14

SE*Responsible

-0.29

0.10

-2.75

0.01*

-0.49

-0.09

Time*Responsible

-0.08

0.05

-1.72

0.09

-0.17

0.01

SE*Monitor

0.10

1.03

0.31

-0.09

0.30

Time*Monitor

0.08

0.04

1.86

0.06

0.00

0.17

SE*Time*Responsiveness

-0.06

0.04

-1.46

0.15

-0.15

0.02

SE*Time*Demandingness

0.03

0.05

0.64

0.52

-0.06

0.12

SE*Time*Responsible

0.12

0.04

2.84

0.00*

0.04

0.21

SE*Time*Monitor

-0.04

0.04

-0.86

0.39

-0.12

0.05

Figure 3.5 Interaction between adolescent self-efficacy and parental responsibility on

frequency of family meals at baseline, 8 weeks, and 16 weeks.

interaction between self-efficacy and time (Hypothesis 1a), or time and any other

parenting factors (Hypothesis 1b). There were no other significant three-way interactions

(Hypothesis 2). However, two significant main effects existed for the frequency of family

mealtime outcome. There was a significant positive relationship between parental

responsiveness and mealtime frequency, Coefficient=0.43, SE = 0.10, p<0.01, indicating

that greater parental responsiveness was associated with greater frequency of family

mealtimes, and remained stable across time. Additionally, there was a significant positive

relationship between parental responsibility for adolescent diet and mealtime frequency,

Coefficient=0.23, SE = 0.10, p=0.02, indicating that greater parental responsibility was

associated with more frequent family meals, and remained stable across time (see Table

3.13). Both findings were consistent with the hypotheses.

3.8 Secondary Outcome Quality of Family Mealtime. Model comparisons for quality

of family mealtime were completed using the same methods as the other models and a

total of three chi-square comparisons were completed (Table 3.14). For the quality of

family mealtime outcome, the best-fitting model was Model 3 (two-way interactions with

time; ꭓ

(20) = 17.46, p<0.01). In other words, model fit was not improved with the

addition of three-way interactions (ꭓ

(28) = 8.87, p=0.35). However, three-way

interactions are included in the final model and effects were interpreted. Results for the

quality of family mealtime indicated a significant two-way interaction between parental

responsiveness and time, Coefficient=0.16, SE = 0.08, p=0.04 (Table 3.15). The plot of

this interaction revealed that quality of family mealtime increases over time for

adolescents with highly responsive parents (Figure 3.6). Alternatively, quality of family

mealtime decreases over 16 weeks for adolescents whose parents practice low

responsiveness.

There was also a significant two-way interaction between parental demandingness

and time, Coefficient=-0.25, SE = 0.08, p<0.01. The result demonstrates that quality of

family mealtime increases over 16 weeks for adolescents whose parents practiced low

demandingness (Figure 3.6). Alternatively, quality of family mealtime decreases over 16

weeks for adolescents whose parents demonstrated high demandingness.

There were no significant three-way interactions (Hypothesis 2) nor any other

significant two-way interactions between self-efficacy and time (Hypothesis 1a) and any

other parenting factors (Hypothesis 1b). However, there was a significant main effect for

parental responsibility, Coefficient=0.35, SE = .18, p<0.05, such that greater parental

responsibility was associated with greater quality of family mealtime and remained stable

across time. This finding was consistent with our hypotheses.

Table 3.14 Hierarchical Approach for quality of family mealtime

Note. Model 1 included covariates and time; Model 2 included covariates, time, predictor

variables (parenting variables and self-efficacy); Model 3 included covariates, time,

predictor variables, and interactions with time; Model 4 included covariates, time,

predictor variables, interactions with time, and three-way interactions with adolescent

self-efficacy, parenting variables, and time.

Table 3.15 Model outcome analysis – quality of family mealtime

Note: “SE” represents self-efficacy.

Model

logLikelihood

Test

Likelihood Ratio

P-value

-1331.73

-13.18.17

1 vs 2

27.13

<0.01

-1309.44

2 vs 3

17.46

<0.01

-1305.00

3 vs 4

8.87

0.35

Estimate

T-value

P-value

Lower

95%

Upper

95%

Intercept

3.36

0.19

17.76

0.00

2.99

3.72

Group Randomization

0.21

0.11

1.81

0.08

-0.02

0.43

Online Randomization

0.11

0.94

0.35

-0.11

0.33

Child Age

-0.13

0.03

-3.82

<0.01*

-0.19

-0.06

Child Sex

0.06

0.12

0.52

0.60

-0.17

0.30

Parent Education

0.19

0.12

1.64

0.10

-0.03

0.42

Parent BMI

-0.01

0.01

1.56

0.12

0.00

0.02

-0.13

0.15

-0.85

0.39

-0.42

0.16

Time

-0.13

0.07

-1.79

0.07

-0.27

0.01

Responsiveness

-0.19

0.17

-1.09

0.27

-0.53

0.15

Demandingness

0.47

0.17

2.71

0.01*

0.14

0.81

Responsibility

0.35

0.18

1.98

<0.05*

0.01

0.69

Monitoring

0.21

0.17

1.24

0.22

-0.12

0.55

SE*Time

0.07

1.06

0.29

-0.06

0.21

SE*Responsiveness

0.23

0.17

1.31

0.19

-0.11

0.56

Time*Responsiveness

0.16

0.08

2.09

0.04*

0.01

0.32

SE*Demandingness

-0.05

0.19

-0.24

0.81

-0.40

0.31

Time*Demandingness

-0.25

0.08

-3.22

<0.01*

-0.40

-0.10

SE*Responsible

-0.15

0.18

-0.86

0.39

-0.50

0.19

Time*Responsible

-0.10

0.08

-1.33

0.18

-0.25

0.05

SE*Monitor

-0.08

0.17

-0.47

0.64

-0.42

0.25

Time*Monitor

-0.05

0.08

-0.67

0.50

-0.20

0.10

SE*Time*Responsiveness

-0.10

0.07

-1.33

0.19

-0.24

0.04

SE*Time*Demandingness

0.02

0.08

0.31

0.75

-0.13

0.18

SE*Time*Responsible

0.12

0.07

1.59

0.11

-0.03

0.26

SE*Time*Monitor

0.04

0.07

0.50

0.62

-0.11

0.18

Figure 3.6 Parental responsiveness by time interactions predicting quality of family

mealtime

Figure 3.7 Parental demandingness by time interactions predicting quality of family

mealtime

CHAPTER FOUR

DISCUSSION

This study examined relationships between adolescent self-efficacy, parenting

factors, adolescent health outcomes (kCal, fat, fruit, and vegetable intake), and family

mealtime outcomes in overweight African American families. A primary aim was to

determine temporal stability of adolescent self-efficacy and parenting factors. It was

hypothesized that increases in adolescent self-efficacy over time (16 weeks) would be

associated with improvements in adolescent health outcomes (decreased zBMI, decreased

kCal and fat intake, increased fruit and vegetable intake) and increased frequency and

quality of family mealtime. However, the results of the study did not support this

hypothesis and there were no significant main effects or interactions with time in

predicting adolescent zBMI, dietary intake (kCal, fat, fruit, and vegetable) or family

mealtime outcomes (frequency and quality). However, the results of the study showed

stability of effects for two parenting factors, responsiveness (kCal intake, fat intake, and

frequency of family meals), and responsibility for adolescents’ diet (quality of family

meals). As expected, greater parental responsiveness was associated with increased

frequency of family meals and increased responsibility was associated with increased

quality of family meals. These effects were not moderated by time, indicating that the

parenting factors were stable across 16 weeks. The results also showed unexpected main

effects, such that increased responsiveness was associated with greater kCal and fat

intake. These findings suggest parental responsiveness and parental responsibility may be

associated with kCal intake, fat intake, frequency of family meals, and quality of family

meals over time. Although there is temporal stability in these parenting variables, the

dietary outcomes were not in the expected direction.

It was also hypothesized that increases in warm, responsive parenting (parental

responsiveness, parental responsibility) would be associated with improved weight

related outcomes (decreased zBMI, decreased kCal and fat intake, increased fruit and

vegetable intake) and increased frequency and quality of family mealtime, while more

demanding, controlling parenting (demandingness, parental monitoring) would be

associated with poorer health outcomes (increased zBMI, increased kCal and fat intake,

decreased fruit and vegetable intake) and poorer family mealtime outcomes (reduced

frequency and quality) over time. Results demonstrated significant relationships for the

zBMI outcome and quality of family mealtime outcome. Time moderated effects for

zBMI were both in unexpected directions. For instance, lower parental responsibility was

associated with decreased adolescent zBMI over time, while higher parental

responsibility was associated with increased adolescent zBMI. Additionally, the

relationship between parental monitoring and adolescent zBMI over time was in an

unexpected direction, showing that higher parental monitoring was associated with lower

zBMI over time and lower monitoring was associated with higher zBMI over time. On

the other hand, some hypotheses for the quality of family mealtime outcome were

confirmed., Results demonstrated that higher parental responsiveness was associated with

greater quality of family mealtime over time, while lower parental responsiveness was

associated with lower quality family mealtimes. Additionally, higher parental

demandingness was associated with lower quality of family mealtime over time. No other

two-way interactions with time were significant.

A second aim of this study was to assess whether parenting factors moderate the

relationship between dietary self-efficacy and adolescent health outcomes (zBMI and

kCal, fat, fruit, and vegetable intake) and family mealtime outcomes (frequency and

quality). It was hypothesized that warm parenting (responsiveness and parental

responsibility) would be related to a more positive relationships between self-efficacy

and health and family outcomes, while demanding parenting (demandingness and

parental monitoring) would be related to a more negative association between self-

efficacy and health and family outcomes. However, three significant three-way

interactions were identified, and the findings were counterintuitive. Specifically, self-

efficacy was associated with decreased kCal and decreased fat intake for individuals with

more demanding parents. Self-efficacy was also associated with fewer family meals

across time for individuals whose parents practiced greater responsibility for adolescent

diet.

4.1 Findings Associated with Weight-Related Outcomes

The current study is one of a few studies that have investigated longitudinal

associations between parental feeding practices and adolescent health outcomes and is the

first study to show a longitudinal relationship between parental responsibility and

adolescent zBMI. Previous cross-sectional research has shown that greater parental

responsibility is associated with lower adolescent zBMI (Loncar et al., 2021). However,

this finding has not been validated in other cross-sectional or longitudinal research.

(Schmidt et al., 2017; Shloim et al., 2015). Despite limited evidence, the responsibility

factor was included in the present study as it was expected to capture adolescent

perspectives regarding parental dietary support. Namely, it was hypothesized that

parental responsibility would be associated with more desirable health and family

outcomes, as adolescents may perceive greater parental responsibility to relate to greater

nurturance and support. The relationship between parental responsibility and adolescent

zBMI was opposite of the hypothesized direction, showing that high parental

responsibility was associated with greater zBMI across 16 weeks. A few factors may

explain this unexpected finding. First, this is one of the only studies to examine these

relationships in an adolescent sample (Kaur et al., 2006; Polat & Erci, 2010; Schmidt et

al., 2017). This is important as interpretation may vary for differing development stages.

For instance, adolescents may feel that parents who are responsible for feeding them at

home, deciding their portion sizes, and deciding which foods are the “right” kind of foods

may have fewer opportunities to increase dietary self-efficacy and self-regulation in these

domains, and subsequently have poorer health outcomes (Bandura, 1977; Hill et al.,

1998; Chu et al., 2013). Alternatively, adolescents who have opportunities for shared

dietary decision-making, autonomy for portions, and have an overall sense of agency in

their diets may have better health outcomes, including healthier zBMI (Dallacker et al.,

2019). Additionally, previous literature has also considered the internal consistency and

reliability of the responsibility measure to be lower than other CFQ subscales for

different populations (Kaur et al., 2006; Polat & Erci, 2010; Shloim et al., 2015).

The present study also demonstrates an interesting finding that adolescents whose

parents practice high monitoring of their diet have lower zBMIs over time, while

adolescents of low-monitoring parents have higher zBMIs over time. Previous research

has demonstrated mixed findings for the relationship between parental monitoring and

adolescent BMI (Burton et al., 2017; Holland et al., 2014; Loncar et al., 2021; Schmidt et

al., 2017; Towner et al., 2015)For instance, Towner and colleagues (2015) found that

greater monitoring from female caregivers was associated with adolescent obesity, while

Burton and colleagues (2017) only demonstrated a significant association between

parental monitoring and younger youth. Studies where African American families were

most represented found no evidence for a relationship between monitoring and adolescent

BMI (Burton et al., 2017; Hennessy et al., 2010; Kaur et al., 2006; Loncar et al., 2021).

However, these studies are cross-sectional and did not assess relationships over time.

This is important as some studies have suggested that parental feeding practices are not

stable over time, implying longitudinal relationships may differ from cross-sectional

relationships. Potential temporal instability of the monitoring variable may explain the

unexpected finding.

The finding adds to previous literature and offers a longitudinal perspective of the

relationship between parental monitoring and adolescent zBMI. Namely, this finding

demonstrates that African American adolescents who report their parents monitor their

sweets, snack food, and high fat food intake, have lower zBMIs across 16-weeks when

compared to adolescents who report fewer monitoring behaviors. This result is

meaningful as it also suggests some monitoring behaviors for adolescents may be

beneficial and relate to better health outcomes (i.e. healthier zBMI). It is important to

consider cultural factors that may influence this finding. Namely, some research asserts

that African American parents use more authoritarian parenting styles and practices when

addressing their adolescents’ diet (Polfuss et al., 2011). Other studies have noted that

authoritarian feeding practices may have different effects for African American

adolescents as they may increase a sense of love and security (Hill et al., 2007).

This study also found a significant relationship between parental responsiveness

and adolescent kCal intake, as well as parental responsiveness and adolescent fat intake.

Literature has asserted that parenting style may affect adolescent health behaviors such as

dietary intake (Berge et al., 2010a; Liang et al., 2016; Rhee et al., 2015). These studies

have noted that greater responsiveness is typically associated with more desirable health

outcomes in children and adolescents. However, few recent publications have assessed

the relationship between kCal or fat intake and parental responsiveness (Haugland et al.,

2019; Kim et al., 2008; Pearson et al., 2010b). The direction of the present findings,

however, were opposite to the hypothesized direction. Specifically, the results indicated

that greater parental responsiveness was associated with greater adolescent kCal intake

and greater fat intake. These unexpected findings may be associated to limitations in

dietary recall data, where additional data may have increased reliability (St. George et al.,

2016).

4.2 Findings Associated with Dietary Outcomes

The current study is the first to assess moderating effects of parenting factors in

the relationship between adolescent self-efficacy and health outcomes (kCal intake, fat

intake) over time. Theoretically, self-efficacy relates to the degree of engagement in

health behaviors, such as self-monitoring dietary intake for weight maintenance or weight

loss (Bandura, 1997, 2004). There have been limited studies assessing relationships

between adolescent self-efficacy and health outcomes, therefore the present study offers

novel perspectives guided by theory. A significant relationship between self-efficacy,

parental demandingness, and time was found, such that self-efficacy related to greater

kCal/fat intake in adolescents with lower parental demandingness and lower kCal/fat

intake in adolescents with higher parental demandingness at baseline. This was contrary

to the hypothesized direction that greater parental demandingness would moderate the

relationship between self-efficacy and kCal/fat intake, resulting in higher kCal/fat

consumption for adolescents with highly demanding parents. While this finding appears

counterintuitive, there may be several factors that influence the finding. One

consideration relates to the items included from the API scale (Jackson et al., 1998).

Specifically, the present study includes three items from this scale, asking adolescents to

endorse to what degree their parents have rules they must follow, tell them when they

have to be home, and know where they are after school. Endorsing these items may

indicate the presence of developmentally-appropriate boundaries and expectations rather

than overly-controlling parenting practices. In so, adolescents who endorse perceived

parental demandingness may have parents who are appropriately engaged in other aspects

of their lives, such as providing nutritional meals and encouraging energy balance. From

this perspective, it may be reasonable that higher demandingness be associated with

lower kCal/fat intake among adolescents. Despite being in an unexpected direction, this

finding provides insight into moderating role of parenting factors on adolescent self-

efficacy and health outcomes.

There were no significant main effects, two-way interactions, or three-way

interactions with either the adolescent fruit or the vegetable dietary outcome. However,

previous research has established relationships between parenting factors, adolescent self-

efficacy, and fruit and vegetable intake (Blissett, 2011; Kremers et al., 2003;

Luszczynska et al., 2016; Pearson et al., 2011a; Quattlebaum et al., 2021). For instance,

Luszcynska and colleagues (2016) found that greater adolescent self-efficacy was

associated with greater fruit and vegetable intake in their cross-sectional analysis

(Luszczynska et al., 2016). Longitudinal analyses have also indicated relationships

between adolescent self-efficacy and fruit and vegetable intake. For instance, Pearson and

colleagues (2011) found that adolescent self-efficacy positively predicted fruit and

vegetable intake one year later (Pearson et al., 2011b). Additionally, many studies that

have assessed the relationship between parenting and adolescent dietary intake have

shown that more authoritative (high responsiveness) parenting was associated with

greater fruit and vegetable intake (Franchini et al., 2011; Kremers et al., 2003; Monge-

Rojas et al., 2010; Pearson et al., 2010b; Watts et al., 2017).

Some factors that may have affected this study’s lack of fruit and vegetable

findings. One important consideration is the amount of dietary recall data that was

collected for the present study. Three dietary recalls were required of each adolescent at

both the baseline (0 weeks) and post-online (16 weeks) timepoints. In this process,

adolescents self-reported the meals they had 24 hours prior and dietary data was

calculated using their report. However, there is growing evidence that more than three

dietary recalls are required to achieve reliability standards. In fact, recent research shows

that ten dietary assessments are needed for data to be reliable, thus there are considerable

limitations with reliability of dietary recalls in this study (St. George et al., 2016). The

limited dietary recall data may have influenced the findings for the fruit and vegetable

outcome.

4.3 Findings Associated with Frequency and Quality Family Mealtime

This study found that parental responsiveness was positively related to frequency

of family meals. This finding is consistent with the hypothesis that more responsive

parenting would be associated with more family meals. This finding is consistent with

previous literature, which demonstrates that more authoritative parenting may coordinate

more frequent family meals (Berge, 2009). In addition to mealtime frequency, this study

found a positive, direct effect between parental responsibility and quality of family

mealtimes. In other words, adolescents who reported that their parents were more

responsible for their diets perceived family mealtimes to be more enjoyable. This finding

was consistent with the hypothesized direction of this relationship. While other studies

have established that authoritative parenting is associated with healthier child and

adolescent dietary intake, no known studies have established a significant and positive

associations between related constructs, parental responsibility and quality of family

mealtime. The finding also demonstrates temporal stability of parental responsibility,

suggesting that this factor remains consistent across timepoints. Taken together, the

findings are particularly meaningful when considering the ripple effects of family

mealtime. Namely, previous studies have demonstrated that eating meals together as a

family may be a predictor of adolescent health (Ardakani et al., 2023; Berge, 2009; Boles

& Gunnarsdottir, 2015; S.M. Robson et al., 2020). For instance, in their recent meta-

analysis, S.M. Robson and colleagues (2020) described evidence that eating together as a

family more often is associated with positive dietary outcomes such as increased fruit and

vegetable intake (S.M. Robson et al., 2020). Other studies have shown direct

relationships between frequency of family mealtime and other health outcomes, such as

adolescent BMI (Berge, 2009). Furthermore, Berge and colleagues (2015) found that

greater frequency of family mealtime in adolescence went on to predict health 10 years

later, demonstrating significantly better health for individuals who had more meals with

their family in childhood (Berge et al., 2015). The findings of the current study provide

support for the relationship between parenting factors and family mealtime, which may

have ripple effects for adolescent health.

This study also found a significant relationship between parental demandingness

and quality of family meals over time in the expected direction. Specifically, the finding

shows that adolescents with more demanding parents perceive mealtime to be lower

quality, while adolescents with less demanding parents report higher quality mealtime.

This is consistent with previous literature that suggests that demandingness may

negatively impact familial interactions (Berge, 2009; Dallacker et al., 2019; Kitzman-

Ulrich et al., 2010). This result is also meaningful as it provides further evidence for the

importance of positive quality family mealtimes.

This study demonstrated moderating effects of parental responsibility on the

relationship between self-efficacy and frequency of family mealtime over time. However,

the hypothesized direction was not fully supported. Specifically, greater parental

responsibility for their adolescent’s diet was associated with more frequent family meals

for adolescents with low self-efficacy (compared to adolescents with high self-efficacy)

for the baseline (0-weeks) and post-group (8-weeks) timepoints. At the post-online (16-

weeks) timepoint, higher parental responsibility was associated with more frequent

family meals compared to adolescents whose parents practiced low responsibility for

their diet. High parental responsibility was associated with greater frequency of family

meals for adolescents with low self-efficacy across timepoints. As previously discussed,

the responsibility measure may have been interpreted differently by adolescents and may

limit adolescents’ opportunities to build self-efficacy and practice health behaviors.

However, it is reasonable to expect that parents who perceive themselves to be more

responsible for their adolescents’ diets may initiate family meals more often. Prior

literature has outlined the potential adolescent health benefits from increased family

mealtime (Ardakani et al., 2023).

As expected, this study found a positive two-way interaction between parental

responsiveness and time, adolescents with responsive parents endorsed better quality of

family meals across time. This is a novel finding as previous research has not outlined the

longitudinal relationship between parental responsiveness and perceived quality of

mealtime in African American families. However, a growing body of literature indicates

the benefits of enjoyable family meals. For instance, Berge and colleagues (2014) found

that when children and adolescents enjoyed family mealtime, they were less likely to be

overweight (Berge et al., 2014b). In fact, Dallacker and colleagues (2019) recently

conducted a meta-analysis where they concluded that quality, even more so than quantity,

of family mealtime is related to adolescent health (Dallacker et al., 2019). This aligns

with established findings that positive familial interactions, such as those during family

meals, promote child and adolescent health (Kitzman-Ulrich et al., 2010).

4.4 Study Limitations and Strengths

There are a few limitations of this study that should be considered when

interpreting the results. Regarding dietary outcomes, additional dietary recalls were

needed to meet a standard of reliability (St. George et al., 2016). While the current study

collected three dietary recalls for adolescents at two timepoints, increased recalls at each

of the three timepoints may have provided further insights regarding relationships

between adolescent self-efficacy, parenting factors, and health outcomes. Regarding

design, future research may expand on the current findings by including observing

longitudinal relationships across longer timespans. Namely, examining relationships over

the longer periods of time may provide additional insights regarding the temporal

stability of variables, moderation effects, and direct relationships between adolescent

self-efficacy, parenting, and health outcomes. More causal study designs would also

expand our understanding of how these factors directly and indirectly influence weight-

related outcomes.

Another limitation of this study relates to the self-efficacy data. As the dietary

self-efficacy data was not imputed and ready for analysis, a self-efficacy for health

behaviors (i.e. exercise) measure was used in its place. While the two measures are

moderately correlated (r = 0.57 – 0.73), use of the specific dietary self-efficacy measure

would provide stronger insights into the tested relationships.

A significant strength of this study relates to the study sample. The entire sample

was comprised of overweight African American adolescents between the ages of 11-16

and a parent or caregiver. Very few studies exist that adequately represent African

American families, and few studies examine relationships in entirely overweight samples.

The current study expands on existing literature by evaluating these relationships in an

underrepresented sample, providing supporting and novel insights regarding relationships

between adolescent self-efficacy, parenting factors, and health outcomes. Lastly, this

study was longitudinal and allowed for the exploration of temporal stability in adolescent

self-efficacy and parenting factors.

Overall, a strength of this study is that it provides meaningful insights into the

complexities of the relationships between parenting, self-efficacy, dietary outcomes, and

BMI outcomes. Findings demonstrate the need for further investigation into these

variables and how they relate to adolescent health and weight-related outcomes.

4.5 Implications and Future Directions

Findings in the present study may guide future research endeavors. An interesting

aspect of the present study is the incorporation of family mealtime outcomes. As

literature grows to assess factors of adolescent health, frequency and quality of family

mealtime are proving to become significant predictors of child and adolescent health

outcomes(Ardakani et al., 2023; Berge, 2009; Berge et al., 2015; Dallacker et al., 2019).

An expansion of the current study may consider the direct relationships between family

mealtime variables and adolescent health outcomes, such as zBMI and dietary intake.

Additionally, future research may consider the relationships between family mealtime

variables and cognitive variables such as self-efficacy and self-regulation.

Additionally, future studies may incorporate different parenting measures. While

the present study focused on analyzing the aspects of parenting style and parental feeding

practices, broader literature emphasizes varying perceptions of parenting factors. For

instance, some developmental literature outlines the role of parental coercion and family

conflict in child/adolescent development (Patterson, 2015). Namely, parental harshness

through coercive behaviors may cause parent-child conflict and influence the

development of child self-regulatory behaviors. Consideration of parenting factors

beyond the scope of parenting style and parental feeding practices may provide valuable

insights into the relationships between parenting and adolescent health outcomes.

More so, further consideration regarding parenting differences with overweight

and obese children/adolescents may contribute to the literature. Namely, research

suggests that parents engage with overweight and/or obese children differently compared

to normal-weight children (Berge et al., 2016). Further investigation regarding the

specific differences in parenting style and parenting behaviors with overweight compared

to normal weight children would provide further context for understanding the role of

parenting in adolescent health.

Overall, continued investigation of factors influencing adolescent health

behaviors and related factors (e.g. self-efficacy and self-regulation) is critical to

determine appropriate interventions and preventative measures to address overweight and

obesity in children and adolescents.

4.6 Conclusion

In summary, childhood overweight and obesity continue to be a significant health

concern and especially affects African American families (Ogden, Carroll, Kit, et al.,

2016). Identifying factors that influence adolescent weight and weight-related behaviors

is essential in creating efficacious interventions to address overweight and obesity.

Literature has demonstrated that parenting factors, such as parenting style and parental

feeding practices, are associated with adolescent weight and related health behaviors.

Additional research has shown that cognitive factors, such as self-efficacy and self-

regulation may also determine adolescent health. More so, these factors may influence

family mealtime variables, which a growing body of research establishes to be related to

adolescent weight and weight-related outcomes. The current study filled a gap in

literature by assessing the temporal stability of parenting factors and adolescent self-

efficacy. It expanded on previous research by assessing longitudinal relationships

between self-efficacy and adolescent health and family mealtime outcomes, as well as

parenting factors and adolescent health and family mealtime outcomes. More so, it

provided insight into the moderating effects of parenting factors in the relationship

between adolescent self-efficacy and health and family mealtime outcomes. However,

only some findings of this study were in expected directions, while other findings were

unexpected. While some moderating effects were determined, they were in

counterintuitive and unexpected. Outside of these interactions, there were no significant

findings relating to self-efficacy. While self-efficacy may be an important determinant of

health behavior engagement and health outcomes, additional research is needed to

provide a clearer understanding of its role. Of the expected findings in this research, there

were significant positive effects of parental responsiveness on quality of family mealtime

over time. A growing body of literature supports the importance of family mealtime and

its implications of child and adolescent development. Future research may further

investigate the family to provide further insights into family environment and its

relationships with adolescent health and development.

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