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On top of that there are many variables: phone calls and communications from social workers, parents, carers, teachers, workers, inquiries as well as emergencies and crucial child protection issues to be dealt with.
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This would enable women with variable phone access or HIV disclosure status to better manage the information provided.
The variables age, phone type, practitioner (all at p<0.001) and condition (p=0.028) were found to be significant predictors.
We have considered the sum of these four ordinal variables: the Phone Score (PS), as a simple aggregation measure.
A fifth variable called phone score will be built as the sum of these four ordinal variables.
Furthermore, when merging calls and SMS messages into one variable (mobile phone use) we lose information about specific exposure.
The results of experiments with real-life (variable) mobile phone EMFs are indeed not identically reproducible, since between successive exposures at any specific location the exact characteristics of the emitted signal are always different.
The other main variables are a phone's weight, size and styling.
Though there is a high correlation between these two variables like mobile phone and the Internet, we regress separately with financial inclusion along with same control variables.
Discrete (cf. Table 1) Citizenship (single or dual) Current citizenship Discrete (cf. Table 1) Income Total salary from regular job Discrete (cf. Table 1) Educational attainment Highest degree obtained Discrete (cf. Table 1) Dependent variables Frequency of phone calls How often do you call your relatives in Senegal?
Of all variables analyzed here, phone numbers had the highest error rates.
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