Determinants of sleep habits in toddlers: Application of planned behavior theory

Abstract

BACKGROUND:

Sleep health is a prerequisite for mental and physical health. The family affects the sleeping habits of the child.

OBJECTIVE:

The purpose of this study was to investigate the theory of mothers’ planned behavior in predicting sleeping habits of toddlers.

METHODS:

The participants of this descriptive-analytical study were 120 mothers of 12- to 36-month-old children living in Razan, Hamadan province, Iran. Data were collected in three stages in order to develop a theory-based tool. Semi-structured qualitative interviews with mothers were conducted to investigate the application of theory in predicting mothers’ intention and behavior (n = 25). The face and content validity of the questionnaire was confirmed by a panel of experts. Test-retest method was used to determine the reliability of the questionnaire at 3 weeks interval (n = 25). Validity of Structural Convergence and Divergence with Factor Analysis, Internal Consent with Cronbach’s Alpha and predictive validity was determined by multiple regression coefficients (n = 120).

RESULTS:

The mean age of the children was 22.8 ± 7.5 months, 55% (66 children) were boys, the mean score of the children’s sleep questionnaire was 49 ± 6, and the children’s sleep duration was 9 ± 1 hour. Theoretical constructs have a positive and direct correlation with each other and with children’s sleep habits, which demonstrates the validity of the theory in predicting toddler sleep habits. Regression analysis showed that perceived behavioral control was the strongest predictor of sleeping habits of toddlers (𝛽 = 0.446) (P = 0.000). The theory of planned behavior can explain 30.5 to 25.7% of the variance of toddler sleep habits.

CONCLUSION:

While recommending more comprehensive studies, the findings of the study emphasize the application of the theory of planned behavior in identifying factors influencing sleep habits and designing child sleep improvement interventions.

Keywords

Theory of planned behavior toddler sleep habits perceived behavioral control

1. Introduction

Proper time, adequate duration, high performance, peace of mind, and alertness during waking hours are among the characteristics of sleep health [1,2]. In families with healthy behaviors, children also have healthy sleep habits [3]. Behavioral factors affecting children’s sleep may include the use of electronic media, television in the child’s bedroom [4], maternal mental health [5], family members’ internal communication, security in parent-child relationships [6]. Common sleep problems in children are more rooted in behavioral problems than medical problems [7]. Every manifest act, consciously or unconsciously, with measurable repetition, intensity and duration is called the behavior [8]. The theory of planned behavior (TPB) is designed to predict individual behaviors. Intention is the most important determinant of behavior and outcome of attitude, subjective norms and perceived behavioral control. Attitude is the result of individual evaluations from the consequences of behavior. Subjective norms are the understanding of social pressure to do or not to perform one’s behavior or mentality to approve or disapprove of important and influential individuals. Perceived behavioral control is influenced by individual self-efficacy, personal abilities, and environmental factors. Unlike the direct relationship between intention and behavior, the effect of perceived behavioral control on behavior is complex. The impact of past behavior is also considered in predicting intention and behavior [9–12]. The power of the theory of planned behavior has been shown to predict health intention and behaviors such as physical activity and diet, and self-reported behavior has been associated with increased predictability [13]. This theory has been successfully applied to the prediction and description of factors affecting children’s sleep (with the exception of toddlers). for example, intention and perceived behavioral control in anticipation of sleep habits among students was statistically significant [14]. In college students, sleep patterns were also predictable with behavioral intention and perceived behavioral control [15]. Therefore, in this cross-sectional study, the theory of planned behavior was used to identify the factors affecting the sleep of toddlers to examine the factors that influence mothers’ behavior (intention, attitude, perceived behavioral control, subjective norms) on toddlers’ sleep habits.

2. Methods

This was a cross-sectional descriptive study that was conducted from January 2016 to February 2016 in health centers of Razan city, Hamadan province, Iran with the aim of determining the role of maternal behavior based on the theory of planned behavior in the sleep habits of 12- to 36-month-old children. A seemingly healthy child from each family participated in the study.

2.1. Research community, samples and sampling process

The study population consisted of all mothers of 12- to 36-month-old children in Razan city of Hamadan province, Iran. With the permission of the Health Deputy, a list of health centers in the city of Rosen (72 centers) was prepared. Twelve health centers and 10 children from each health center were randomly selected. Inclusion criteria included: Voluntary participation in the study; literacy; children aged between 12 and 36 months; children with physical and mental health (a health confirmation of both health records and a clinical examination by specialist physician was required); full time residence in Razan; children must live with both parents, have had vaccinations and a supplementation program (Multivitamin or A + D and Iron) according to the national plan; lack of physical and mental disorders in the parents. Exclusion criteria included: not wanting to participate in the study; children with diagnoses of acute or chronic illnesses, as confirmed by a specialist physician; continuation of a child’s medical treatment; physical presence of a parent’s disability; parental dependence on drugs, alcohol and psychotropics.

2.2. Data collection tools

Three questionnaires were used:

Demographic information questionnaire (11 questions about age and sex of the child, birth rate, birth weight, age, parental education and occupation, and number of children).

The 33-item Child Sleep Habits Questionnaire (CSHQ) assessed children’s sleep [16]. Questions were scored on a three-point Likert scale and higher scores indicated sleep problems [17]. The validity and reliability of this tool has been demonstrated in other studies [17,18]. Falahzadeh et al. also confirmed the internal consistency and reliability of the questionnaire items using Cronbach’s alpha coefficient and test-retest coefficient, respectively [19].

The mothers’ behavioral questionnaire based on TBP was designed to predict the sleeping habits of toddlers [20] and was scored on a five-point Likert scale. Data were collected in three stages.

2.2.1. First stage

The semi-structured qualitative interviewing of mothers aimed to investigate mothers’ behavior based on the structures of planned behavior theory in predicting sleeping habits of toddlers in Iran. By random sampling of mothers with toddlers residing in the villages of Razan city of Hamadan province, 25 mothers who were willing to complete an open questionnaire were asked about their toddler’s sleep. The questions were designed according to the international definition of the theory of planning behavioral constructs, after analysis, they were categorized into five theoretical constructs [21]. Tool readability, face and content validity were reviewed and validated by a panel of experts (including 4 specialists in the theory of planned behavior and 2 sleep specialists). According to expert panel recommendations 4 questions of intention structure and subjective norms were removed. The final version of the tool consisted of 37 questions.

The mother's attitude toward the child's sleep habits was assessed by 14 questions (range 14 to 70). For example, “timely and adequate sleep has a positive effect on a child’s health”. Mothers’ perceived behavioral control of children’s sleep habits was assessed with 10 questions (range of 10--50 points). For example, “child’s sleeping habits are a natural issue and cannot be programmed to control them”. Abstract norms were assessed with 4 questions (range of 4--20 points). For example, “people who matter to me say that it is not necessary for a child to sleep regularly and at a specific hour”. Structural evaluation of maternal intention to sleep habits of the child was performed with 4 questions (range of 4–20 points). Such as, “I’m going to improve my child’s sleeping habits in the next month”. Past behavior was assessed with 5 questions (range of 5--25). For example: “In the past month, the child was asleep until 9pm”.

After evaluating the suitability of 37 questions for performing exploratory factor analysis, this test was performed using SPSS version 23. Elemental analysis revealed the existence of five constructs of intention, attitude, abstract norm, and perceived behavioral control and past behavior with a specific value greater than 1, which explain 76.8%, 57.1%, 50.6%, 60.2% and 60.1% of the variance, respectively. The results of this analysis confirms the use of the designed tool.

2.2.2. Second stage

Test-retest participants were recruited from rural health centers. 25 mothers completed the TBP questionnaire twice in three weeks. The optimum reliability coefficient was considered above 0.7 (Table 1).

Table 1
Test-retest coefficients and internal consistency for TBP structures in toddler sleep behaviors

Structure Item Cronbach’s alpha r ^∗

Past behavior 5 0.851 0.913

Behavioral intention 4 0.869 0.885

Perceived behavioral control 10 0.842 0.871

Abstract norm 4 0.793 0.823

Attitude 14 0.816 0.812

Sleep habits 33 0.756 0.806

Structure	Item	Cronbach’s alpha	r ^∗
Past behavior	5	0.851	0.913
Behavioral intention	4	0.869	0.885
Perceived behavioral control	10	0.842	0.871
Abstract norm	4	0.793	0.823
Attitude	14	0.816	0.812
Sleep habits	33	0.756	0.806

^∗Significant at P < 0.01.

2.2.3. Third stage

In determining sample size, alpha was considered equal to 0.05, power 0.80 and population correlation coefficient 0.20. Eventually a sample of 120 people was found to be suitable for this tool [22].

2.3. Method of collecting samples

The present study is part of a Master’s thesis approved by the Ethics Committee of Qazvin University of Medical Sciences (Ethics Code: IR.qums.REC.1396.347). After obtaining the consent of the Research Deputy of Qazvin University of Medical Sciences and the Deputy of Health of Hamadan University of Medical Sciences and coordination with the Behvarzes, mothers were invited to participate in the study by telephone. The mothers went to the health centers on their own suggested schedule, and the research team, while explaining the research goals, obtained consent from the mothers to participate in the study voluntarily. When explaining how to answer the questions, the research team emphasized the confidentiality of the information and the anonymity of the questionnaires. The mothers then answered the questions in the presence of the research team for approximately 25--30 minutes. The presence of the researcher was intended to ensure that mothers fully and accurately answered and prevented possible ambiguities regarding questions and answers.

2.4. Data analysis

After entering data in SPSS software version 23, normal distribution of data was performed using Kolmogorov–Smirnov test and preliminary analysis to ensure non-violation of normal assumptions, linearity and uniformity of distribution. In addition to descriptive statistics and exploratory factor analysis, independent t-test, multiple linear regression, Pearson correlation coefficient and path analysis were used. Significance level was considered less than 0.05 in the present study.

3. Results

3.1. Demographic characteristics of participants

After the third stage, the tool was designed for 120 infants (54 girls and 66 boys) residing in Razan city of Hamadan province, Iran. The mean age of the children was 22.8 5 7.5 months, 55% (66) boys, 60% (72) infants (12–24 months), 25.8% (31) single children, 67% (80 persons) term and 84% (101 people) birth weight was 2500 grams and more. The mean current weight of the children was 12066 ± 2113 with a weight range of 18000 to 8700 g. The mean age of mothers was 29.42 ± 5.18 years, 18.3% had college education and 11.7% were employed. All the fathers (100%) were employed. They had a mean age of 34.83 ± 5.05 years and 10.18% of them had a college education.

3.2. Toddler sleep information

The mean score of children’s sleep questionnaire was 49 ± 6, with a sleep duration equal to 9 ± 1 hours with a range of 13–6 hours. 69% of the children had adequate sleep (11–13 hours per 24 hours), 17% had insufficient sleep and 14% had sleepiness.

3.3. Results of data analysis

Independent t-test was performed to compare the mean scores of the constructs of the theory of planned behavior based on demographic characteristics, although the difference between the mean scores was significant (P < 0.001). However, because of the very small effect size, there is little practical difference. Independent t-test was performed to compare the mean scores of the toddler’s sleep habits based on demographic characteristics. There was no significant difference between toddler sleep habits scores based on child gender, child birth, child age, number of children, birth weight and mothers’ occupation. Pearson correlation test scores of the constructs of theory of mothers’ planned behavior and children’s sleep habits showed a significant positive correlation between mothers’ intention and children’s sleep habits. The strongest correlations between child’s sleep habits were with perceived behavioral control (𝛾 = 0.556) and mothers’ behavioral intention (𝛾 = 0.552) (P < 0.05) (Table 2).

Table 2
Pearson correlation coefficients of maternal TBP structures and toddler sleep habits (n = 120)

Item 1 2 3 4 5

1 Sleep habits -

2 Behavioral intention ^∗∗0.452 -

3 Perceived behavioral control ^∗∗0.563 ^∗∗0.524 -

4 Abstract norm ^∗∗0.311 ^∗∗0.344 ^∗0.192 -

5 Attitude ^∗∗0.174 ^∗∗0.369 ^∗0.167 ^∗∗0.308 -

Item		1	2	3	4	5
1	Sleep habits	-
2	Behavioral intention	^∗∗0.452	-
3	Perceived behavioral control	^∗∗0.563	^∗∗0.524	-
4	Abstract norm	^∗∗0.311	^∗∗0.344	^∗0.192	-
5	Attitude	^∗∗0.174	^∗∗0.369	^∗0.167	^∗∗0.308	-

^∗Significance level is less than 0.01. ^∗∗Significance level is less than 0.05.

3.4. The power of predicting mothers’ TPB questionnaire on toddlers’ sleep habits

The predictive power of the instrument was evaluated using multiple linear regression. Model 1 is a framework for predicting behavioral intention. Model 2 is a complete picture of the theory of planned behavior with a specification of the path between intention, perceived behavioral control, and behavior.

3.4.1. Model 1

Multiple linear regression was modeled with retrospective elimination strategy to predict behavioral intention by perceived behavioral control structures, abstract norms, and attitudes. The primary criterion is to enter a predictor into this model (F ≥ 0.05) and to remove a predictor (F ≥ 0.10). All three predictors were significant for behavior (P = 0.000). Overall, the predictors produced (P < 0.05), F (3,119) = 36.091, R ² = 0.305. Therefore, this model predicts 30.5% of the variance of mothers’ behavioral intention for sleep habits in the studied toddlers.

3.4.2. Model 2

Linear regression with retrospective elimination method was used to predict behavioral intention theory and perceived behavioral control on the variable outcome of mothers’ behavior. The primary criterion is the probability of F for entering a predictor into the model (F ≤ 0.05) and for removing the predictor (F ≥ 0.10). Both behavioral intention (P = 0.003) and perceived behavioral control (P = 0.000) were identified as significant predictors of maternal behavior. (P < 0.05), F (3.119) = 63.01, R ² = 0.257 explained 25.7% of the variance in participants’ behavior. Table 3 summarizes the parameter estimates for model 1 and 2. Figure 1 illustrates the final model for predicting intention and behavior in the samples. Regression analysis results showed that perceived behavioral control was the strongest predictor of toddler sleep habits (𝛽 = 0.446) (P = 0.000) (Table 3).

Table 3
Regression model results in a sample of 120 toddlers

Variables B Sd B 𝛽 T $R_{\mathit{adjusted}}^{2}$ P value^∗

Model 1: Constant −1.16 0.506 - −2.522 0.305 0.024

Perceived behavioral control 0.085 0.017 0.412 7.760 0.000

Subjective norms 0.064 0.021 0.163 3.143 0.000

Attitude 0.051 0.019 0.216 3.710 0.000

Model 2: Constant 214.517 19.344 - 13.815 0.257 0.001

Behavioral intention 16.832 7.226 0.211 2.640 0.003

Perceived behavioral control 8.530 1.120 0.446 7.462 0.000

Variables	B	Sd B	𝛽	T	$R_{\mathit{adjusted}}^{2}$	P value^∗
Model 1: Constant	−1.16	0.506	-	−2.522	0.305	0.024
Perceived behavioral control	0.085	0.017	0.412	7.760		0.000
Subjective norms	0.064	0.021	0.163	3.143		0.000
Attitude	0.051	0.019	0.216	3.710		0.000
Model 2: Constant	214.517	19.344	-	13.815	0.257	0.001
Behavioral intention	16.832	7.226	0.211	2.640		0.003
Perceived behavioral control	8.530	1.120	0.446	7.462		0.000

^∗Significant at P < 0.05.

Fig. 1.

Routine analysis of constructs of mothers' planned behavior theory for predicting toddlers’ sleep habits. (Regression weights and coefficients of 𝛽 and R2 are adjusted.)

4. Discussion

Several studies have been performed on the sleep habits of Iranian children, but none of them examined toddlers [3,22–24]. The current study is the first study to determine the power of constructs of mothers’ theory of planned behavior in predicting the sleeping habits of Iranian toddlers, and it extends the application of this theory in predicting sleeping habits of toddlers. To achieve this goal, a three-stage valid and reliable questionnaire was designed. Childhood sleep habits were assessed using the CSHQ questionnaire. The mean score was 49 ± 6, which is similar to the study by Richard et al. (46.8 ± 74.22). In both studies, there was no correlation between the scores of the child’s sleeps habits questionnaire and the age and sex of the children [18]. The prevalence of childhood insomnia in the present study is similar to that of Plancolin et al. [25]. The results of the study by Zhang et al., as in the present study, show that the toddler’s age and weight are not correlated with the duration of nighttime sleep [26]. Theory constructs have a positive and direct correlation with each other and with sleeping habits of children, indicating the validity of the theory of planned behavior in predicting maternal intention and behavior in relation to sleeping habits of toddlers. Mothers’ perceived behavioral control is the most influential variable on intention and behavior. Hence, reinforcing it can help improve children’s sleep habits and educational interventions based on mothers’ perceived behavioral control are recommended. Perceived behavioral control is an important and effective factor in conducting behavior. Assessment of perceived behavioral control can help predict these behaviors when individuals are uncertain about their ability to perform specific behaviors [27]. Perceived behavioral control is a reflection of parental beliefs about the existence or absence of resources and opportunity to develop a child’s sleeping habits. When parents feel that they have control over a child’s sleep habits, they are aroused to develop the child’s proper sleep habits and do it in the face of challenges [28]. The study of sleep habits in students showed that the theory of planning behavior is significantly able to predict intention and behavior. Intention and perceived behavioral control were effective in predicting behavior [14]. In college students, the theory of planned behavior was successful in explaining sleep habits so that perceived behavioral control and subjective norms were predictors of intention [14,15,29] and attitude was not significantly related to intention [14]. Similar to the present study, in other health related issues, the highest correlation was found between perceived behavioral control and intention (𝛾 = 0.81) [30]. According to the theory of planned behavior, behavioral intention is predicted by attitude, perceived behavioral control, and subjective norms. In model 1, these indirect variables were identified as significant predictors of behavioral intention. Perceived behavioral control is the strongest predictor of mothers `behavioral intention in toddlers’ sleep habits (𝛽 = 0.446), second in attitude (𝛽 = 0.216) and last in subjective norms (𝛽 = 0.163) is located (P > 0.05). Overall, these variables predicted 30.5% of the variance of mothers’ behavioral intention in sleep habits in the studied toddlers. In this theory, behavioral intention is a direct predictor of behavior. On the other hand, the less the person’s voluntary control over their behavior, the role of perceived behavioral control is stronger [31]. In the two-intention model and perceived behavioral control, it was able to predict 25.7% of toddlers ’sleep habits, while perceived behavioral control (𝛽 = 0.446) was approximately twice as strong as the mothers’ behavioral intention (𝛽 = 0.211) and was effective in predicting children’s sleep habits. Comparison of the variables of the two models shows that programs aimed at improving mothers’ perceived behavioral control will be able to improve sleeping habits of toddlers. Perceived behavioral control, perceptions of the ease of doing behavior that affected by personal self-efficacy and personal abilities (skills, awareness, information) and environmental factors (social support, socioeconomic status). Mothers’ perceived behavioral control of toddler sleep seems to be a constant pre-sleep program, such as snacking, brushing, storytelling, and reading books that make a child ready and provisory for sleep, plans the toddler’s life and enhances the mother’s ability to control the toddler’s sleeping habits. Better sleep, earlier hours of sleep, less sleep delay, decreased night awakening, increased sleep duration are known effects of the fixed bedtime program at 0--5 years of age [32]. According to the definition of perceived behavioral control, when mothers become familiar with the effects and implementation of a fixed bedtime program and the environmental conditions are favorable, toddlers’ sleep habits improve and their children’s sleep problems are lessened. Hence, it seems that the role of fixed bedtime programs before sleep in perceived behavioral control of mothers determines sleeping habits and problems of toddlers. It can also help mothers to obey to an appropriate timing of meals for babies, taking a bath close to the bedtime, obey a routine schedule for bedtime, provide an appropriate environmental condition for the baby bedroom including temperature, humidity and light, reduce the daytime sleep and treat some medical disorders such as allergy, respiratory infection, gastroesophageal reflux and so on in babies [2,33–36].

5. Conclusion

According to the results of the present study, assessment of mothers' planned behavior can be used to predict toddler sleep habits. Perceived behavioral control of mothers is the most important predictor of affective behaviors on child's sleep habits and mothers' intentions. In this study, mothers' intentions also predicted behaviors leading to child's sleep habits. The results of this study can be used to plan and develop strategies to improve sleeping habits of toddlers and emphasized the reinforcement of intention and perceived behavioral control in parents.

5.1. Weaknesses and strengths of the study

Limitations of the present study are small sample size, cross-sectional study and data collection using questionnaires. On the other hand, there are inherent limitations to TPB because it does not explain emotional processing. The core hypothesis of the TPB is that human's base behavior-related decisions on logical thinking processes, while unhealthy behaviors may be rooted in psychological problems. Selection of healthy children is also one of the limitations of this study because disease conditions affect sleep patterns. One of the strengths of the study is the choice of toddler age, which is the time of the formation of one's sleep habits and has received little attention in previous studies.

5.2. Recommendations

Sleep habits in toddlers are the basis for the development of sleep habits at an early age. It is therefore recommended to pay attention to the sleep habits of toddlers in future studies to prevent sleep problems in children and adolescents. Objective methods such as polysomnography as the gold standard should be used to reduce toddler sleep error. On the other hand, although sampling in this study was done randomly. But, due to the limited sample size, the results can be generalized to other communities in question, so more studies with larger sample sizes are recommended. Since cross-sectional studies are not able to detect causal relationships, it is desirable to design longitudinal and prospective interventions.

Footnotes

Acknowledgements

We would like to thank all the teachers, students, experts, parents and others who helped us with this research.

Conflict of interest

None to report.

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