The Norbeck social support questionnaire (NSSQ) [
Despite the advantages of being a network based inventory, House and Kahn [
However, though effective in removing the effects of network size variability, as fully detailed below, Norbeck [
The purpose of this paper is twofold: first, using three different data sets, we evaluate Norbeck’s [
The conceptual basis for the NSSQ [
One reason for its widespread use is that unlike other network-based support inventories, the NSSQ is completed by the participant without input from an interviewer. This makes it ideal for use in large-scale studies such as mailed surveys. Because of this self-report feature, the NSSQ requires a unique layout. Specifically, participants are first asked to list from 1 to 24 network members “who provide personal support for you or who are important to you” and then specify their relationship (spouse, parent, friend, etc.). After completing the network list, they are instructed to successively turn the half pages and rate each listed network member (0–4) on six functional support questions measuring three types of support: affect, affirmation, and aid (see Table
NSSQ Items.
Functional designation | item |
---|---|
Affect1 | How much does this person make you feel liked or loved? |
Affect2 | How much does this person make you feel respected or admired? |
Affirm1 | How much can you confide in this person? |
Affirm2 | How much does this person agree with your actions or thoughts? |
Aid1 (short term) | If you needed to borrow $10, a ride to the doctor, or some other immediate help, how much could this person usually help? |
Aid2 (long term) | If you were confined to bed for several weeks, how much could this person help you? |
Normative data (
Because support ratings for each network member are summed, support scores (range = 0–576) vary greatly due to network size alone. Thus, the above participant with seven immediate family members functionally inflates his/her support score. In fact, in the three samples [
It is likely that aid’s lower correlations with network size are the result of more participants giving some network members aid ratings of 0 than giving 0’s for affect or affirmation ratings. When this happens, the participant has effectively dropped that person from their network, and thus reduced the influence of network size on that support score. This happens most often with aid, because some participants list network members who may like (affect) and agree with (affirmation) them but be unable to provide tangible help (aid) such as children, elderly parents, and peripheral network members. In fact, in the present study’s third sample [
In summary, though NSSQ support scores are meant to measure quantity of support, they have two determinants of variability: support ratings and network size. Therefore, raw support scores cannot be taken at face value but should be viewed as support ratings
Averaging is not a problem when participants rate all network members uniformly highly or lowly. For example, Participant A lists 7 highly supportive network members, and Participant B lists 14 equally supportive members. B’s score (305) is higher than A’s (154) only because she listed more network members. However, A’s and B’s averaged support scores (A (
In a typical NSSQ network, only a few supporters give large amounts of all three types of support and the others contribute in varying degrees, and this reflects reality. That is, some network members make one feel loved and/or are good confidants but cannot offer tangible support and vice versa. This pattern is typified by Participant C: like B, Participant C has a relatively large network (14), but unlike B, her network members’ ratings were more varied. C rated 7 network members highly on most support questions but varied the ratings of the other 7 network members giving some high and some low ratings for some types of support. Though both A and C each have 7 highly supportive network members and C has 7 additional network members giving some support, C’s averaged score (
Of course, it is possible that this “deflation” of averaged scores happens at all network sizes. In fact, if averaging lowered scores consistently for all participants, then lowered scores due to averaging would be the norm and would result in true regressions to the mean. Thus, as is the case with uniformly high or low ratings, if all participants
Nevertheless, though Norbeck’s [
Is there a statistically significant negative correlation between averaged total functional support scores (entire network) and number in network?
In addition, are there statistically significant negative correlations between averaged affect, affirmation, and aid scores (entire network) and number in network?
Does using averaged total functional support scores provide a measure less infected with extraneous variance and thus produce a more efficient measure than raw total functional support scores? Do averaged total functional support scores yield higher powers than raw scores produced under the same conditions?
Similarly, do averaged affect, affirmation, and aid scores provide an analysis with a higher power than respective analyses with raw scores?
With institutional review board approval, a secondary analysis was conducted on data from three different samples [
All women were community dwelling adults. Table
Study samples’ parametrics compared with Norbeck’s [
NSSQ variables | Norbeck [ | Sample 1 ( | Sample 2 ( | Sample 3 ( | ||||
Mean | Mean | Mean | Mean | |||||
Network number | 10.9 | 5.9 | 10.45 | 5.16 | 10.93 | 5.23 | 11.38 | 5.19 |
Affect and affirmation* | 127.2 | 72.7 | 128.32 | 69.49 | 133.16 | 68.62 | 137.78 | 65.71 |
Aid | 53.1 | 33.4 | 55.95 | 28.63 | 54.42 | 29.10 | 58.18 | 28.82 |
Total functional support | 179.4 | 102.1 | 184.56 | 94.76 | 187.57 | 94.21 | 195.96 | 91.41 |
*Note: Norbeck summed affect and affirmation scores in this report.
Using PASW 18 [
In order to answer these research questions, PMRS [
Using G* power 3 [
Results are presented in Table
However, this is not true for averaged aid scores. In all three samples, there are statistically significant decreases in averaged aid support scores as network size increases. These results are most likely due to the aforementioned high percentage of participants who rated some network members 0 (none at all) for one or both of the aid questions. When participants scored a network member as providing 0 aid, it was most often for network members mentioned later in the network list. That is, it appears that participants begin completing the list of network members by nominating their closest supporters followed by more peripheral supporters. Thus, with the exception of young children and elderly parents, these close supporters are likely able to offer more tangible help than the others. When rating members as providing 0 aid, participants already reduced the influence of network size, and averaging penalized them further, because the denominator was not adjusted to account for this. Averaging does indeed unduly lower aid scores of participants as network number increases.
Correlations of averaged support scores with network number.
Averaged total functional support | Correlation with network number | |
---|---|---|
Sample 1* | −.09 | .24 |
Sample 2** | −.04 | .50 |
Sample 3*** | −.08 | .26 |
Averaged affect | ||
Sample 1 | −.08 | .34 |
Sample 2 | −.09 | .14 |
Sample 3 | −.03 | .72 |
Averaged affirmation | ||
Sample 1 | −.03 | .70 |
Sample 2 | −.01 | .83 |
Sample 3 | −.01 | .93 |
Averaged aid | ||
Sample 1 | −.24 | .003 |
Sample 2 | −.15 | .02 |
Sample 3 | −.17 | .02 |
*
Results are presented in Table
However, averaged aid scores did not perform as well as raw aid scores. The gains in power were modest (.15 and .20) for samples one and three, while power actually decreased in sample two by .19. Thus, in light of results of research questions 1 and 2 showing the statistically significant lowering of averaged aid scores as network size increases and the equivocal effect on power of a test correlation, use of averaged aid scores is not recommended.
Raw and averaged support scores correlations with PMRS and resultant power.
Total functional support | Correlation | Power | Change in power | |
---|---|---|---|---|
Sample 1* | ||||
Raw scores | −.15 | .06 | .47 | |
Averaged scores | −.31 | <.0001 | .97 | ↑.50 |
Sample 2** | ||||
Raw scores | −.15 | .02 | .68 | |
Averaged scores | −.21 | .001 | .93 | ↑.25 |
Sample 3*** | ||||
Raw scores | −.06 | .41 | .13 | |
Averaged scores | −.20 | .006 | .79 | ↑.66 |
Sample 1 | ||||
Raw scores | −.13 | .10 | .37 | |
Averaged scores | −.29 | <.0001 | .96 | ↑.59 |
Sample 2 | ||||
Raw scores | −.16 | .01 | .74 | |
Averaged scores | −.24 | <.0001 | .98 | ↑.24 |
Sample 3 | ||||
Raw scores | −.07 | .37 | .16 | |
Averaged scores | −.19 | .01 | .75 | ↑.59 |
Sample 1 | ||||
Raw scores | −.16 | .04 | .52 | |
Averaged scores | −.30 | <.0001 | .97 | ↑.45 |
Sample 2 | ||||
Raw scores | −.13 | .04 | .56 | |
Averaged scores | −.20 | .002 | .91 | ↑.35 |
Sample 3 | ||||
Raw scores | −.07 | .38 | .16 | |
Averaged scores | −.21 | .003 | .83 | ↑.67 |
Sample 1 | ||||
Raw scores | −.13 | .10 | .37 | |
Averaged scores | −.17 | .04 | .57 | ↑.20 |
Sample 2 | ||||
Raw scores | −.13 | .03 | .56 | |
Averaged scores | −.10 | .12 | .37 | |
Sample 3 | ||||
Raw scores | −.04 | .59 | .08 | |
Averaged scores | −.09 | .23 | .23 | ↑.15 |
*
Averaging reduces the influence of varied network size, but Norbeck [
However, Norbeck’s [
Data for this study were collected with funding from PSC-CUNY (1999 and 2003), the Wyeth Ayerst Women’s Health Scholar Award from the American Nurses Foundation (2002), and Sigma Theta Tau (Upsilon, 1999).