Adolescent Sleep Health Belief Scale

Authors

Purpose

In the realm of pediatric health psychology, there has been a historical overreliance on instruments that measure the symptoms of poor sleep rather than the cognitive antecedents that cause it. The Adolescent Sleep Health Belief Scale was developed to fill this exact methodological gap. While existing tools might tell a clinician that a teenager is only sleeping five hours a night, they fail to explain *why* the teenager isn't motivated to change that behavior. This instrument provides the 'why' by mapping the adolescent's internal decision-making landscape regarding their sleep habits.

This tool is particularly vital for school nurses, public health researchers, and clinical psychologists tasked with designing Preventive Interventions. Behavior change is rarely achieved through education alone; it requires altering an individual's risk appraisal and self-efficacy. By utilizing this scale, practitioners can identify which specific belief domains—such as a lack of perceived severity regarding sleep loss or overwhelming perceived barriers to going to bed early—are deficient in a target population. Consequently, interventions can be tailored to shift these specific cognitive appraisals, drastically improving the efficacy of health promotion programs.

Construct

The psychological construct captured by this scale is 'sleep-related health beliefs,' which is theoretically anchored in the Health Belief Model (HBM). The HBM is a foundational framework in health psychology that posits that an individual's willingness to engage in a health-promoting behavior is dictated by a specific constellation of cognitive appraisals. Rather than viewing sleep as a passive biological drive, this construct treats Sleep Hygiene as an active, motivated behavior subject to conscious and subconscious evaluation.

The scale operationalizes this construct through six distinct but interacting dimensions. 'Perceived susceptibility' and 'perceived severity' measure the threat appraisal—how vulnerable the adolescent feels to the consequences of sleep deprivation and how serious they believe those consequences to be. 'Perceived benefits' and 'perceived barriers' capture the decisional balance, weighing the functional advantages of good sleep against the social or environmental obstacles preventing it. Finally, 'self-efficacy' evaluates the adolescent's confidence in their ability to execute healthy sleep behaviors, while 'motivation' assesses their intrinsic drive to prioritize rest amidst competing adolescent demands.

Validity

The validation process for this instrument demonstrates a rigorous approach to both content and construct validity. To ensure the initial item pool accurately reflected the theoretical dimensions of the Health Belief Model, the researchers engaged a panel of ten experts in Public Health Nursing. This expert consensus yielded an exceptional Scale-Level Content Validity Index (S-CVI) of 0.94, well above the standard threshold of 0.90, indicating that the items are highly representative of the target constructs. Items failing to meet the 0.80 threshold at the item level (I-CVI) were appropriately discarded prior to structural testing.

Construct validity was evaluated through Exploratory Factor Analysis (EFA), a necessary step when mapping a new item pool to an established theoretical framework. The sampling adequacy was excellent, as evidenced by a Kaiser-Meyer-Olkin (KMO) value of 0.92. The EFA successfully distilled a massive 81-item pool down to a lean 46-item structure that perfectly mirrors the six theoretical dimensions of the HBM. Together, these six factors explain 57.7% of the total variance in adolescent sleep health beliefs, which is a robust explanatory proportion for a multidimensional psychological construct.

Reliability

Reliability testing for the instrument revealed strong internal consistency across the majority of its dimensions. The Cronbach's alpha coefficients for the subscales ranged from 0.69 to 0.92. The highest internal consistency was observed in the perceived susceptibility (0.92), perceived severity (0.90), and perceived benefits (0.90) subscales, indicating that items within these domains are highly intercorrelated and reliably measure the same underlying concept.

It is worth noting for graduate Students analyzing this profile that the perceived barriers subscale yielded the lowest alpha at 0.69. In psychometric scale development, barrier subscales frequently exhibit lower internal consistency because the obstacles to a behavior (e.g., homework, screen time, social pressure) are inherently diverse and may not strongly correlate with one another. To further substantiate the scale's stability, a split-half reliability analysis was conducted, yielding coefficients of 0.92 and 0.78 for the two halves. This confirms that the instrument maintains structural integrity and consistency across its entire length.

Factor Analysis

The researchers utilized Principal Components Analysis (PCA) with an oblique rotation method to uncover the latent structure of the item pool. The choice of an oblique rotation is psychometrically sound and theoretically appropriate here, as the dimensions of the Health Belief Model (such as self-efficacy and perceived benefits) are expected to correlate with one another in real-world psychological functioning. Forcing an orthogonal rotation would have artificially constrained these natural relationships.

The iterative factor reduction process was aggressive and methodologically rigorous. The researchers systematically eliminated 35 items that either failed to achieve a primary factor loading of at least 0.32 or exhibited problematic cross-loadings (a difference of less than 0.10 between factors). The resulting 46-item model is remarkably clean, with final factor loadings ranging from 0.42 to 0.80. The variance is well-distributed across the construct, with perceived susceptibility accounting for the largest share (15%), followed by severity (9.9%) and benefits (9.8%), confirming that threat appraisal and outcome expectancies are the most dominant statistical features of the scale.

Subscales

Instrument

Scoring & Interpretation Guidelines

Sample

The psychometric evaluation utilized a sample of 509 ninth and tenth-grade high school Students from Antalya, Türkiye. After data cleaning to remove incomplete responses, the final analytical sample consisted of 494 Students. This sample size comfortably exceeds the recommended 5:1 to 10:1 participant-to-item ratio required for robust exploratory factor analysis.

Adolescent Sleep Health Belief Scale Items