Cyber relationship motives scale development and validation of a questionnaire

SciELO - Scientific Electronic Library Online OBJECTIVES: to develop a questionnaire to measure factors associated with for PA (α=, ICC=) and social support and motives for engaging in PA .. Neighborhood environement walkability scale for youth (NEWS-Y): reliability abd relationship with physical activity. Identifying Problematic Internet Users: Development and Validation of the . well as a relationship between personality types and Internet use [6,]. For example, Amiel and Sargent developed the Internet Motives Questionnaire [21], which . This questionnaire was designed based on the screening scale for computer. Items 42 - 59 Development and Validation of a Questionnaire to Assess the Effect of Online . evidence that examine the relationship between use of the internet and internet behavior – was patterned after the scale used by Kumar et al to study EBP, interest and motivation to engage in EBP, educational knowledge and.

The sample was selected in two stages: The minimum sample size was determined using an intraclass correlation coefficient greater or equal to 0. This resulted in a sample of subjects for the analysis of reproducibility and subjects for factor analysis of questionnaire. The interns received a manual containing the study protocol and conducted a pilot study, under the same conditions as the main study, as a way of standardizing data collection.

The adolescents themselves responded to the questionnaire, in their classrooms, during class time, as previously instructed by an intern. Two other interns circulated to help and clear up any doubts the adolescents may have had. The adolescents who did not participate, either because their parents or guardians did not permit them, or because they were not in school on the day of the data collection, were considered to be losses. To characterize the study sample, the adolescents responded to questions on demographic sex and age and socioeconomic aspects schooling of mother and father [primary school incomplete, primary school completed, high school incomplete, high school completed, higher education incomplete, higher education completed], economic class, possession of material goods, number of paid servants in the household and schooling of head of household.

The individuals were grouped into the following classes: A four-point semantic differential scale was used, with the following binary pairs of adjectives: The items were written in such a way as to incorporate the obstacles to the practice of physical activity frequently reported by the adolescents. The environment scale contained items measuring the following aspects of the neighborhood: The validity of the construct was analyzed using exploratory factor analysis to establish the number of factors that should be extracted.

For this, the criterion suggested by Kaiser was used: Then, orthogonal varimax rotation was performed21 Items with a factor loading equal to or greater than 0. The data used were those from the first application of the questionnaire. Reproducibility was estimated using the repeated measurements method test-retestwith an interval of a week between the two tests.

When the questionnaire was first applied, the adolescents received an envelope containing two copies of the questionnaire, both with the same bar-code. The adolescent took out one of the copies, sealed the envelope and returned it to the intern responsible for the questionnaire. When applied the second time, the adolescent received the envelope with his or her name on it, took off the label and filled in the copy of the questionnaire, following the same instructions as the first time, provided by the same intern.

The scores for each item, sub-scale and total scale were compared for the two applications of the questionnaire using the intra-class correlation coefficient ICC. Overall scores and scores on each section were calculated, considering only those who responded to all the items for the respective factors.

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The sum of the scores attributed to each response to the items numbered 1 to 4 was calculated, inverting the scale in the case of responses to items where the higher number indicated an aspect less favorable to physical activity. The data were entered in duplicate into the EpiData 3. The "validate double entry" was used to identify typing errors, which were subsequently corrected by consulting the original questionnaires.

Statistical analysis was carried out using the Stata Prior to analysis, a "map" of "impossible" or "improbable" combinations of results was drawn up using the same program and the data were reviewed according to these parameters.

All adolescents aged under 18 received permission from their parents or guardians to take part in the study. Results Initially, adolescents were selected.

Of these, 14 did not agree to participate in the study and two were not given permission by their parents or guardians. The final sample comprised adolescents aged between 14 and 19 years.

Most of the adolescents studied were female Table 2 presents the results of the exploratory factor analysis of the questionnaire.

The results of the factor analysis showed that the attitude measurement was a single factor, with five items, all with a factor loading greater than 0. The proportion of total explained variance was In the case of self-efficacy with regard to physical activity, two factors were extracted: The proportion of explained variation for each factor was Two items were excluded for having a low factor loading: In the case of social support two factors were identified: The factor loa-dings were almost all greater than 0.

For the perceived environment three factors were identified: The proportion of variance explained by each factor was Table 3 shows the results of the reliability analysis internal consistency and test-retest reproducibility for the variables covered by the questionnaire. The levels of reproducibility for the overall score and factors or sections were equal to or greater than 0. Discussion The results of this study show that the scales attitude of adolescents regarding engaging in physical activity, self-efficacy and social support of parents and friends regarding physical activity and perceived environment to measure the factors associated with physical activity under study were factorially valid, of satisfactory internal consistence and highly reproducible.

This study revealed a number of positive aspects that deserve mention. The study was based on a random sample of adolescents in public and private high schools, with a broad range of ages years and with different socio-economic characteristics, which means that the findings can more easily be generalized.

The internal validity was strengthened by the use of various operational and statistical procedures, which effectively demonstrated the validity and reliability of questionnaire. Another strong point was the sample size.

For exploratory factor analysis, it is recommended that there be a ratio of 1: Attitude is one of the main categories in the Theory of Planned Behavior. However, exploratory factor analysis revealed the presence of a single factor, and the proportion of explained variance was These results were weaker than those reported by Lee et al.

Based on the results of the factor analysis, two items were excluded: The low contribution of these items can be explained by the fact that the climate is not such an important factor when engaging in physical activity in the Northeast of Brazil, and lack of time may be more an excuse than an obstacle to engaging in physical activity, and is more commonly found among adults than among adolescents.

The factor analysis identified the presence of two factors for the self-efficacy scale: The results of the study of self-efficacy regarding physical activity point in different directions. Some studies show that there is a single factor8,13,14 while others identify two25 or three.

As this measure expresses the perception of subjects regarding their capacity to overcome obstacles to engaging in physical activity, differences between the obstacles reported by adolescents20,26 may also contribute to these results. Another factor to be considered concerns the procedures used for statistical analysis: These results are similar to those of some studies8,13,14 and higher than those found by Saunders et al.

The reproducibility coefficients for the self-efficacy scores were higher than 0. The results of the present study were similar7,11 or higher than those reported in other studies. In the present study, the social support scale had 12 items, distributed between two factors.

While factor 1 grouped together all the items relating to social support from friends, factor 2 those relating to social support from parents, each containing six items. The levels of reproducibility for the measures of social support were high.

The ICC attained values close to friends: These findings were higher than those reported in other studies. Therefore, we can assume the existence of a generation that has grown up with the latest technologies from a very young age [ 12 ] and that Internet use is an extremely widespread phenomenon. This situation can be clearly explained by the fact that the Internet is a convenient source of information, social contacts, education, shopping, and recreational activities [ 6 - 10 ] that simplifies everyday life.

The Internet also has a negative side. Furthermore, different studies in several countries show that for 1. Initial results from longitudinal studies even give rise to the suspicion that the disorder is highly stable [ 18 ].

Regarding the relationship between the Internet and all areas of life [ 5 - 7 ] and the suggested DSM-5 criteria for Internet addiction [ 11 ], the duration someone spends online does not appear to be a valid criterion. Thus, getting to know the motives behind adolescent Internet consumption is important. Concerning motives for media use in general, McQuail [ 1920 ] assumes 4 basic motives: Recent research regarding the motivations of Internet use in particular found the existence of instrumental motives, such as information seeking and social interaction, as well as a relationship between personality types and Internet use [ 621 - 28 ].

There are, however, a number of gaps in current research. First, not much is known about affectivity, which plays an important role in understanding problematic Internet use. In fact, there are instruments for measuring Internet addiction and instrumental motives for using the Internet. Infor example, Young [ 29 ] developed the first instrument for measuring Internet addiction, the Internet Addiction Test IATwhich was translated into various languages and validated in different samples [ 30 - 33 ].

Also, the previously mentioned Internet Motives Questionnaire assesses motives that are more instrumental as they target the affective function the Internet serves for adolescents. According to the motivation model of McClelland [ 34 ], affective change is assumed to be the driving force behind human behavior. Hence, striving for positive affect and escaping or relieving a dysphoric mood is seen as the basis of motivational Internet behavior and thus, according to the DSM-5, a criterion for Internet use disorder [ 11 ].

Second, none of the studies were based on a theoretical framework defining the dimensionality of motives for Internet use a priori.


The MOGQ is based on a theoretical approach, although this model was developed by observing online players. Thus, the questionnaire is specific to Internet gaming and, therefore, not applicable to Internet use motives in general.

One promising approach that includes affectivity and allows the classification of the motivation behind human behavior was proposed by Cox and Klinger [ 3637 ]. The Motivational Model of Alcohol Use assumes that people display a certain behavior to achieve expected or desired effects [ 38 - 42 ].