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When past behavior was added to the model, intention was a significant predictor for the hedonic behavior, but not for the distal behavior.
At baseline, participants (N = 279) completed a questionnaire designed to measure the following cognitive constructs derived from the extended TPB model: intention, attitude, subjective norm, perceived behavioural control, self-identity, anticipated regret, moral norm and descriptive norm.
In the ASE model, intention is also determined by social-influence and self-efficacy.
For the model, intention to undertake a falls assessment and multifactorial intervention at a falls and balance clinic was the response variable.
In the overall model, intention was the only significant predictor of parents' use of online information to manage their child's health care, F (5, 170) = 8.98, p < .001 (see Table 2).
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According to Ajzen's (2002) TPB model, intentions are determined by subjective norms, personal attraction or attitude and perceived behavioural control.
His interests include AI, Semantic Web, KR, NLP, big social data analysis, affective and cognitive modeling, intention awareness, HCI, and e-health.
Within social cognition models, intention is a strong predictor of behaviour.
Generalised linear mixed models (intention-to-treat) will assess outcomes for treatment (maintenance vs. control), time (baseline, 6-month and 12-month) and the treatment-by-time interaction.
Within the mixed effects models, intention-to-treat (ITT) analyses were conducted, meaning that all recruited parents (n = 135, including drop-outs and the few TF-CBT cases failing to reach the acceptable level of fidelity) were analyzed in the condition into which they were originally randomized.
Michael Bratman (1987) would query this by noting that the belief/desire model of intention fails to adequately model the organizational role intentions play in practical deliberation.
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