Predicting sleep hygiene: a reasoned action approach

Tagler, Michael J.; Stanko, Kathleen A.; Forbey, Johnathan D.

doi:10.1111/jasp.12411

Cited by 21 publications

(34 citation statements)

References 47 publications

(66 reference statements)

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“…The results showed that attitudes, particularly the variable Attitude to multitask, play an important role in our model; this seems to be in line with a substantial literature showing that behavior is strongly influenced by personal attitudes (Fishbein and Ajzen, 1975;Ajzen and Albarracín, 2007;Belleau et al, 2007;Jaccard, 2012). The value (positive or negative) that individuals attribute to a particular behavior affects the engagement in risky behaviors (Neighbors et al, 2013), also in the specific case of road behavior (Iversen and Rundmo, 2002;Dahlen et al, 2005).…”

Section: Discussionsupporting

confidence: 86%

Mobile Phone Use “on the Road”: A Self-Report Study on Young Drivers

et al. 2021

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BackgroundExtensive research showed that multitasking negatively affects driving performance. Multitasking activities can range from talking and texting to listening to music; particularly among young drivers, multitasking behavior is caused mainly from mobile phone use while driving which is one of the main causes of road accidents.ObjectiveThe main purpose of this study was to investigate whether some variables (e.g., Sensation-Seeking, preferences of Multitasking) could affect mobile phone use while driving in young drivers and whether any gender differences were present among the examined variables.Setting and participantsThe sample consists of 424 Italian students (56% males) with an age range of 18–21 years. A self-report questionnaire was specifically developed to assess variables such as: Attitude toward Multitasking, Perceived Self-efficacy in Multitasking, Accident Risk Perception, General Multitasking Habits, and Sensation Seeking.ResultsThrough SEM modeling, we found the attitude to multitasking while driving to be largely explained by the considered variables. Using multigroup analysis (MGSEM), the model we developed appears to be suitable for explaining the behaviors of both male and female young drivers. Furthermore, data comparison showed that females were more likely to risk perception toward multitasking, and risk perception when using a mobile phone while driving, while males obtained higher mean scores in Sensation Seeking, Perceived Self-Efficacy in Multitasking, and in Multitasking caused by mobile phone use while driving.ConclusionOur research showed how some variables may influence the inclination of some subjects to engage in multitasking while driving. Furthermore, we discussed the importance of considering these variables in the implementation of effective road safety education projects on driving multitasking.

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Section: Discussionsupporting

confidence: 86%

Mobile Phone Use “on the Road”: A Self-Report Study on Young Drivers

et al. 2021

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“…sleeping 8–9 hours each night; Robbins and Niederdeppe, 2014). Finally, in another study with college students, the IMB constructs predicted a significant amount of variance for six sleep-related behaviours: sleeping 8 hours per night (59%), having a consistent sleep and wake schedule (75%), avoiding caffeine before bed (71%), avoiding alcohol before bed (78%), exercising regularly (70%) and avoiding large meals before bed (75%) (Tagler et al, 2017). Research that operationalises and tests the IMB is still emerging, and more research is needed to understand how the model can be applied to other health behaviours.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the determinants of sugary beverage consumption among overweight and obese adults: An application of the integrative model of behavioural prediction

Collado-Rivera

Branscum

Larson

et al. 2017

Health Education Journal

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Objective: The objective of this study was to evaluate the determinants of sugary drink consumption among overweight and obese adults attempting to lose weight using the Integrative Model of Behavioural Prediction (IMB). Design: Cross-sectional design. Method: Determinants of behavioural intentions (attitudes, perceived norms and perceived behavioural control [PBC]) and sugary drink consumption (intentions, skills/abilities, environment and PBC) were evaluated using data collected at a weight loss clinic in a southwestern US city ( n = 338). Determinants of attitudes, injunctive norms, descriptive norms and PBC were evaluated using salient beliefs, which were derived from an elicitation study. Results: Using structural equation modelling, two separate models were evaluated. Both models had good fit (combined model – Comparative Fit Index [CFI] = .970, Tucker–Lewis Index [TLI] = .921, Root Mean Square Error of Approximation [RMSEA] = .062; expanded model – CFI = .966, TLI = .911, RMSEA = .060) and accounted for a significant amount of variance for intentions (40.7%–42%) and sugary drink consumption (16.2%). Conclusion: The IMB appears to be an effective model for planning health education interventions. Health practitioners should operationalise behaviour change techniques and strategies that target attitudes, perceived norms and PBC using the salient beliefs evaluated in this study.

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“…An example of negative SS comes from a study on sleep deprivation by Tagler, Stanko and Forbey (2017). The raw correlation between perceived behavioural control and actigraphy sleep duration was positive (r = .18), however the standardized partial coefficient was negative (β = -0.07).…”

Section: Types Of Statistical Suppressionmentioning

confidence: 99%

Incidence and interpretation of statistical suppression in psychological research.

Gutierrez¹,

Cribbie²

2021

Canadian Journal of Behavioural Science / Revue canadienne des

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Suppressors are third variables that increase the predictive power of one or more predictors by suppressing their irrelevant variance when included in a regression model. Although theoretically and statistically useful, no research has addressed the frequency or interpretation of statistical suppression (SS) in the psychological literature. Two studies explored the nature and interpretation of SS. In the first study, regression analyses were reviewed to determine the frequency with which SS occurs in psychological articles published in 2017. Results indicate that approximately one-third of articles showed evidence of SS, although researchers did not acknowledge or attempt to interpret the SS. The second study reviewed articles containing the keyword 'suppression' to assess the interpretations provided by researchers that identified SS.Results indicate that most researchers do not attempt to classify or interpret SS. Therefore, although SS is common in psychology, scarcely any attempts are made to identify, classify, and/or interpret it.

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Predicting sleep hygiene: a reasoned action approach

Cited by 21 publications

References 47 publications

Mobile Phone Use “on the Road”: A Self-Report Study on Young Drivers

Mobile Phone Use “on the Road”: A Self-Report Study on Young Drivers

Evaluating the determinants of sugary beverage consumption among overweight and obese adults: An application of the integrative model of behavioural prediction

Incidence and interpretation of statistical suppression in psychological research.

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