State versus action orientation and compliance during the COVID-19 pandemic in Indonesia

Analysis of Community Compliance With the Covid-19 Health Protocols: A Quantitative

“…The more information obtained the knowledge possessed will be wider. In [20] used TPB and found that information sources positively influence prevention behavior. State policy-oriented people cannot selfregulate their behavior to comply with the COVID-19 protocol.…”

“…A statement item is considered valid if its correlation coefficient with other items (ρ item ) is above or equal to 0.3 and the construct measured in the questionnaire has a coefficient greater than or equal to 0.6 [10]. Easy to get masks 0.63 𝑋 13 Availability of hand washing facilities in public areas 0.67 𝑋 14 Have been positive for COVID-19 0.33 𝑋 15 Families in the same house have been positive for COVID-19 0.34 𝑋 16 Friends/relatives from different homes have been positive for COVID-19 0.42 𝑋 17 Trust the effectiveness of the mask 0.64 𝑋 18 Trust the effectiveness of washing hands 0.63 𝑋 19 Trust the effectiveness of social distancing 0.60 𝑋 20 Affordable mask price 0.49 Cronbach Alpha 0.89…”

From intentions to action: An integrative review of action control theory and research

“…The AOD-scale first appeared in German and English (Kuhl, 1994). In subsequent years, the scale has been translated into at least 16 additional languages, including Bengali (Chatterjee et al, 2018), Chinese (Song et al, 2006), Croatian (Niemivirta et al, 2001), Dutch (Koole & Jostmann, 2004), Farsi (Calero et al, 2007), Finnish (Niemivirta et al, 2001), French (Bouzidi & Gendolla, 2022), Greek (Papantoniou et al, 2010), Indonesian (Elia et al, 2022), Japanese (Sakuma & Sato, 2008), Polish (Marszał-Wiśniewska, 2002), Portuguese (Branco et al, 2015), Russian (Shlyapnikov, 2020), Spanish (Calero et al, 2007), Turkish (Peker & Meşe, 2021), and Vietnamese (Helmke & Tuyet, 1999). Across these languages, the AOD-scale has consistently shown adequate internal consistency, with Cronbach's alphas typically ranging between .60 and .80.…”

Public awareness of and opinions on the use of mathematical transmission modelling to inform public health policy in the United Kingdom

“…As the success of public health policy often depends upon the cooperation of the public, it is important that the public perception of scientific advice, in this case specifically mathematical modelling, is understood. Much of the research into public opinions throughout the COVID-19 pandemic has related to vaccine hesitancy [7][8][9] or adherence to public health and social measures [10][11][12][13]. Although Marshall et al [14] interviewed members of the public regarding Test, Trace and Isolate policies with a view to improving assumptions underpinning mathematical modelling, respondents were not explicitly asked about their perceptions of modelling.…”

“…As the success of public health policy often depends upon the cooperation of the public, it is important that the public perception of scientific advice, in this case specifically mathematical modelling, is understood. Much of the research into public opinions throughout the COVID-19 pandemic has related to vaccine hesitancy [ 7 – 9 ] or adherence to public health and social measures [ 10 – 13 ]. Although Marshall et al .…”