measuring social isolation in older adults_development and initial validation of the friendship...

7/22/2019 Measuring Social Isolation in Older Adults_development and Initial Validation of the Friendship Scale

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GRAEME HAWTHORNE

MEASURING SOCIAL ISOLATION IN OLDER ADULTS:

DEVELOPMENT AND INITIAL VALIDATION OF THE

FRIENDSHIP SCALE

(Accepted 23 May 2005)

ABSTRACT. Although there are many excellent published scales measuring social

isolation, there is need for a short, user-friendly, stand alone scale measuring felt

social isolation with good psychometric properties. This study reports the develop-

ment and preliminary validation of a short, user-friendly scale, the Friendship Scale.

The six items measure six of the seven important dimensions that contribute to social

isolation and its opposite, social connection. The psychometric properties suggest

that it has excellent internal structures as assessed by structural equation modelling

(CFI = 0.99, RMSEA = 0.02), that it possesses reliability (Cronbach a = 0.83)

and discrimination when assessed against two other short social relationship scales.Tests of concurrent discriminant validity suggest it is sensitive to the known corre-

lates of social isolation. Although further work is needed to validate it in other

populations, the results of this study suggest researchers may find the Friendship

Scale particularly useful in epidemiology, population surveys or in health-related

quality of life evaluation studies where a parsimonious measure of felt social support

or social isolation is needed.

KEY WORDS: loneliness, social connectedness, social isolation, social

relationships, social support

INTRODUCTION

Social isolation refers to living without companionship, social sup-

port or social connectedness. It is the absence of significant others

someone interrelates with, trusts, and turns to in time of crisis. It is

associated with poorer health-related quality of life (HRQoL), life

meaning, levels of satisfaction, wellbeing and community involve-

ment (Cantor and Sanderson 1999). The socially isolated suffer worse

health status, have a higher consumption of health care resources

(Ellaway et al., 1999) and have poorer outcomes from acute inter-

ventions, such as cardiovascular surgery (Ruberman et al., 1984;

Social Indicators Research (2006) 77: 521548 Springer 2006

DOI 10.1007/s11205-005-7746-y


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Williams et al., 1992; Farmer et al., 1996). In addition there are

associations between social isolation and mental illness, distress,

dementia, suicide and premature death (Berkman and Syme, 1979;Turner, 1981; House et al., 1982; Lester and Yang, 1992; Kawachi

et al., 1996; Fratiglioni et al., 2000; Rokach, 2000; Ellis and Hickie,

2001).

The key correlate of social isolation is personal relationships

(Polansky, 1985; Maxwell and Coebergh, 1986; Dykstra, 1990, 1995;

Mullins et al., 1996; Plopa, 1996; Gierveld, 1998). Other correlates

include network characteristics such as neighbourhood friendliness

and social initiation, geographic location, living alone or homeless-ness, and ethnicity (Polansky, 1985; Cutrona, 1986; Lewin Epstein,

1991; Straits Troester et al., 1994; Mullins et al., 1996; Scheier and

Botvin, 1996; Gallagher et al., 1997; Gierveld, 1998). Both physical

and mental health status are also predictive of social isolation (Cobb,

1976; Thoits, 1982; Mullins et al., 1996; Plouffe and Jomphe Hill,

1996), as are aging communication losses (Retsinas and Garrity,

1985; Maxwell and Coebergh, 1986). Other correlates include eco-

nomic resources such as employment status and income (Polansky,1985; Maxwell and Coebergh, 1986; Lewin Epstein, 1991; Mullins

et al., 1996; De Jong-Gierveld and van Tilburg, 1999).

It is widely accepted that the prevalence of social isolation is be-

tween 325%. It is a stereotype of later life that there is a network of

loneliness, social isolation and neglect (Victor et al., 2000; Baltes and

Smith, 2002) related to difficulties with mild cognitive impairment,

performing activities of daily living, declining health status, partner

loss, and institutionalization (van Oostrom et al., 1995).The measurement of social isolation is important in studies of

older adults because it may influence their participation in and re-

sponse to public health interventions as well as being an outcome in

its own right. There are, however, several barriers to its measurement;

a major barrier may be questionnaire length.

As evaluation of public health interventions becomes routine,

instrument batteries are increasingly being used. Given that many

elderly people are frail, it is important that batteries are as parsi-monious as possible to minimise response resistance since this cor-

relates with questionnaire length (Dillman, 1978; Yammarino et al.,

1991). Additionally, there are psychometric reasons for parsimony

related to the validity of measurement. These two issues suggest it is

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important to develop short measures (Pedhazur and Schmelkin,

1991). Examples include the SF-12 from the SF-36 (Ware et al., 1995;

Ware et al., 1996), the WHOQOL-Bre` f from the WHOQOL-100(WHOQoL Group, 1996, 1998), the Hearing Participation Scale from

the Glasgow Health Status Inventory (Hawthorne and Hogan, 2002),

and the short form of the Social Support Questionnaire, SSQ6, from

the SSQ (Sarason et al., 1987b).

Although there are many published instruments measuring social

isolation, these are generally long scales designed to measure multiple

constructs, they may invoke response resistance because the items are

negative in tone, they are embedded within other instruments, or theymay have poor psychometric properties. As such their application is

limited in the situations described above. There is need for a short

general scale that is both user-friendly and that has excellent mea-

surement properties.

This paper describes the development of such a scale, the

Friendship Scale (FS).

METHODS

The data reported here are from the World Health Organization

Quality of Life Groups (WHOQOL Group) WHO QOL-OLD

study, aimed at measuring the quality of life (QoL) of older adults.

The study involves over 20 WHOQOL Field Centres around the

world. Each Field Centre undertakes a core research activity that

is common. There is, however, the opportunity for Centres todevelop their own research agendas; in this case measuring the

social isolation of older adults.

Participants

The recruitment strategy was designed to recruit older adults across

the health spectrum, since an axiom of psychometrics is that instru-

ment development samples should be drawn from the populations inwhich the measure will be used. Four older adult cohorts, defined as

those over 60 years, were recruited. The overall recruitment rate was

63% of those in scope; data were available for 77% of those who

agreed to participate. The total number of participants was 829.

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The first cohort was older adults living in supported accommo-

dation, hostels or nursing homes. A research assistant asked residents

to participate. Those who indicated their willingness were deliveredthe questionnaire package which was collected a week later, after self-

completion. Of the 157 residents approached, 122 agreed to partici-

pate and 96 completed the questionnaire. The recruitment rate was

79% of those who agreed to participate or 61% of those were con-

tacted. This HOS (hostel) sample comprised 12% of study partici-

pants.

The second cohort comprised hospital outpatients (recruited

through checking medical records for those with chronic disability) orthose attending day hostel support groups (recruited through snow-

balling of group membership). One hundred and thirty-three cases

were approached, and 78 agreed to participate. Sixty-eight ques-

tionnaires were completed. The recruitment rate of the OUT (out-

patients) cohort was 51% of those contacted or 87% of those who

agreed to participate.

The third cohort was older veterans. Many veterans report diffi-

culties with general social relationships, although they may have closelinks within the veteran community. Advertisements were placed in

Mufti, the Australian Returned and Servicemans League magazine,

and Tapis, the Australian war widows magazine. Of the 164 re-

sponses, 130 veterans or their wives/widows participated; a response

rate of 79% of responders. The MAR (magazine respondents) cohort

was 16% of the study sample.

To recruit a healthy community sample the Victorian electronic

telephone directory was used. Cold calling of randomly selectedtelephone numbers identified households with an older adult. Those

who agreed to participate were posted a self-complete questionnaire.

Of the 1018 households with an older adult, 713 agreed to participate

and 535 returned completed questionnaires; a participation rate of

75% of those within scope or 53% of all households with an older

adult. The COR (community older random sample cohort) com-

prised 65% of study participants.

Measures

The questionnaire package comprised the WHOQOL-Bre` f, questions

from the proposed FS, the 4-item version of the Geriatric Depression

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Scale (GDS, DAth et al., 1994), the Assessment of Quality of Life

(AQoL) utility measure (Hawthorne et al., 1999, 2001), the SF-12

health status scale (Ware et al., 1995), socio-demographic items and aconsent form.

The 4-item version of the GDS (DAth et al., 1994) was designed

for screening elderly patients in general practice to identify those with

depression. It comprises 4 dichotomous items. The cutpoints are 1

indicating an uncertain diagnosis and 2 indicating probable

depression.

The WHOQOL-Bre` f is a QoL instrument comprising 24 items in

four domains: Physical (7 items), Psychological (6 items), Social (3items) and Environment (8 items) (WHOQoL Group, 1996, 1998).

Additionally, there are two global overall QoL items. All items are

rated on a 5-point scale, scoring is by summation and scores are

presented as percentages. The WHOQOL-Bre` f has been used in

studies of mental health and aging (Herrman et al., 2002a; Amir and

Lev-Wiesel, 2003; Chan et al., 2003).

The Assessment of Quality of Life (AQoL) utility instrument

comprises five dimensions: Illness, Independent Living, Social Rela-tionships, Physical Senses and Psychological Wellbeing (Hawthorne

et al., 1999, 2000). It uses the latter four for computing the utility

score ranging from )0.04 (worst possible HRQoL) to 0.00 (death

equivalent HRQoL) to 1.00 (full HRQoL). It has previously been

used in studies of aging (Osborne et al., 2003) and mental health

conditions (Goldney et al., 2000b; Herrman et al., 2002a; Hawthorne

et al., 2003).

The SF-12 has 12 items, which are weighted during scoring fortheir contribution to either physical (PCS) or mental health (MCS)

(Ware et al., 1995; Ware et al., 1996). Items are concerned with the

performance of particular functions. PCS and MCS scores are pre-

sented as T-scores (McCall, 1922) where the norms are 50 (sd = 10).

US weights have been used. The SF-12 has been used in mental health

and older adults studies (Everard et al., 2000; Taylor et al., 2000;

Herrman et al., 2002b; Jackson and Burgess, 2002).

Friendship Scale items

The relationships reviewed above between social isolation and health

conditions have been explained by numerous theories of social



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support, which may be grouped into three key theories: (a) that the

social milieu affects responses to stress and that where there is a mis-

match in social milieu fit, stress may lead to health conditions (Cassel,1976); (b) that social support provides a buffer when people are in

crisis, thus the absence of social support may remove this buffer

leading to health conditions (Cobb, 1976); and (c) attachment theories

which state that childhood experiences predispose adult social network

behaviour (Bowlby, 1971). Clearly, all three theories are related.

Based on these theories, social isolation can be defined as living

without companionship, having low levels of social contact, little

social support, feeling separate from others, being an outsider, iso-lated and suffering loneliness.

This definition suggests that there are seven dimensions to the

construct, and that social isolation can occur where these are trans-

gressed. These dimensions, drawn from the literature, are: (a) an

absence of sharing of feelings or being intimate with a significant

other or others (Weiss, 1974; Russell et al., 1980; Cutrona, 1986;

Sherbourne and Stewart, 1991; Lugton, 1997; Hawthorne et al., 1999;

Smith, 2003); (b) the (in)ability to relate to others (not just the ab-sence of opportunity) with a particular emphasis on what it is that the

relationship provides (Henderson et al., 1980; Rose et al., 2000;

Lauber et al., 2004); (c) being unable to ask others for support when

it is needed, perhaps due to the perception of being a burden to others

(Sarason et al., 1987a; Sherbourne and Stewart, 1991; WHOQoL

Group, 1998; Kissane et al., 2001); (d) having no social networks,

regardless of whether these are for receiving or giving support

(Sarason et al., 1987a; Lee and Robbins, 1995; Victor et al., 2000); (e)being separate or isolated from others in social settings, including

being unable to perform social roles (Ware et al., 1993; Hawthorne

et al., 1999; Rokach, 2000); (f) being isolated from others, whether

through difficulties in communication or social inadequacy (Lee and

Robbins, 1995; Lugton, 1997; Victor et al., 2000); and (g) being alone

or suffering loneliness, including how a person perceives their posi-

tion in relation to others (Russell et al., 1980; Sarason et al., 1987a;

Rokach, 2000; Victor et al., 2000).Obviously, social isolation is a multidimensional construct, and

each of these dimensions should be measured in a comprehensive

instrument. There are numerous operationalizations of this construct,

as the following few examples show. The UCLA Loneliness Scale

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measures personal and social levels of relationships (Russell, 1982;

Russell et al., 1980). The Social Connectedness Scale (Lee and

Robbins, 1995) measures connectedness, affiliation and companion-ship through negative items confronting the respondent with their

losses. Rather more positively, the MOS Social Support Survey

(Sherbourne and Stewart, 1991) defined social support as the fre-

quency with which companionship or assistance was available, and

the short form Social Support Questionnaire defined it as those who

could be counted on (Sarason et al., 1987a). The WHOQOL-100

Social domain was concerned with relationship satisfaction (WHO-

QoL Group, 1998). Others have focused more on nurturing, alliancesand intimacy (Weiss, 1974; Russell, 1982; Russell et al., 1984; Cut-

rona, 1986), while the Social Relationships scale of the AQoL defined

it as the performance of intimate, family and friendship roles

(Hawthorne et al., 1999, 2000).

These differences (and many others can be found) suggest there are

competing perspectives on the construct, including difficulties in

defining what should be measured. Because the construct is multi-

dimensional, the different approaches suggest that its measurementmay be difficult. This can be illustrated by two measures, developed

20 years apart. The Inventory of Socially Supportive Behaviours

(Henderson et al., 1980) comprised 52 items for interview adminis-

tration, located in 6 scales. Confirmatory factor analysis revealed that

while some scales were unidimensional and reliable others were not.

More recently, Rokachs work defined five subscales of loneliness:

emotional distress, social inadequacy and alienation, growth and

discovery, interpersonal isolation and self-alienation. These weremeasured by 82 items accounting for just 36% of the variance

(Rokach, 2000).

Where the dimensions or subscales of social isolation are inade-

quately conceptualized and defined, to group them together into

summated scales will almost certainly result in instruments with poor

psychometric properties. For example, there is evidence that the

Social domain of the WHOQOL-Bre` f suffers this problem because it

consists of three disparate items measuring satisfaction with personalrelationships, friendships and sex lives, where the satisfaction with the

sex item is particularly difficult (Norholm and Bech, 2001; Min et al.,

2002).



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Perhaps the issues above explain Bowlings conclusion made over

10 years ago but seemingly still applicable that There is currently no

assessment scale which comprehensively measures the main compo-nents of social network and support with acceptable levels of reli-

ability and validity (Bowling, 1991, p. 122). A key issue which might,

perhaps, partly explain this situation relates to the perspective of

measurement. The studies reviewed above may be grouped into those

that provide objective assessments of social isolation based on

observation of social conditions (e.g. for a review see Berkman and

Glass (2000)) and those that assess it from the individuals perspective,

i.e. perceived social support (e.g. see Sarason et al. (1987b)). Whilstboth perspectives are valid, the position taken in this paper is that it is

the subjective experience of the individual that has primacy. This

perspective is consistent with the World Health Organizations com-

mitment to the individuals perception of their position in life in the

context of the culture and value systems in which they live and in

relation to their goals, expectations, standards and concerns (WHO-

QoL Group, 1993).

Items from the instruments cited above were reviewed andde novoitems covering each of the seven dimensions written. To ensure

simplicity, item stems were made short and friendly, like those in the

Social Connectedness Scale (Lee and Robbins, 1995) and the

Nottingham Health Profile (Hunt et al., 1981; Hunt et al., 1985;

Hunt et al., 1989). To reduce response resistance to items that may

confront respondents with an awareness of their losses, items were

written from the point of view of having friends and social support.

To prevent acquiescent response bias (Crowne and Marlowe, 1960;Furnham and Henderson, 1982) a mixture of positive and negative

items were written. During item construction, several different ver-

sions were constructed and considered. These were iteratively

reviewed by both older adults and the authors colleagues and

modified until final versions were agreed.

Regarding item responses, a Guttman-type response scale was

prepared because most people do not experience isolation. To over-

come end aversion the worst possible outcome (no social interactionat all) was represented by the lowest level on the response scale,

recognising this implied that few people would actually endorse this

level.

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Finally, the timeframe was set at 4 weeks because this provided an

estimate that was stable rather than one which fluctuated where a

short timeframe was specified, yet not so long as to involve issues ofmemory recall or distortion.

The final version of the Friendship Scale (FS) is presented in the

Appendix. Scoring involves reversal of items 1, 3 and 4 followed by

summation across all items. The score range is 024. A high score

represents social connectedness and a score of 0 complete social

isolation. A computerized scoring algorithm is available from the

author.

Data analysis

Data from the four cohorts described above were pooled. For

reporting the psychometric properties of the FS the sample was

randomly divided into half. The first half was used as the construc-

tion sample and the second half for the confirmatory sample.

Construction sample psychometric tests were principal component

analysis (PCA), item-rest-of-test correlations (IRTC), and internalconsistency (Cronbach a). To overcome data skew, reciprocal log

transformations were used; even so, the items remained marginally

skewed. Because PCA does not provide a unique mathematical model

(Nunally, 1967), the analyses were repeated 20 times, sampling (with

replacement) 50% of cases from the construction dataset. This pro-

vided mean estimates and 95% confidence intervals.

For the confirmatory analyses, AMOS (Arbuckle and Wothke,

1999) was used for a structural equation model (SEM) analysis; thecriteria for fit was based on the root mean square error of approxi-

mation (RMSEA < 0.05, Browne and Cudeck, 1993). Tabachnick

and Fidell (2001) report that when using AMOS, discrepancies may

occur in sample sizes of 200 or less with asymptotically distribution-

free SEM models. In this study, the confirmatory sample was just

under double this number of cases (n = 374). Partial credit item

response theory (IRT) was used to determine item difficulties (And-

rich, 1978; Masters, 1982); this provided an estimate of the order inwhich the various components contributing to social isolation are

progressively reported, as well as the relationship between the scale

items.



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For concurrent validation tests, the full dataset was explored using

correlation, Cohensq, analysis of variance (ANOVA), Fishers Exact

Test and odds ratios. Data were analyzed using SPSS (SPSS, 2003),AMOS (Arbuckle and Wothke, 1999) and Conquest (Wu et al.,

2000).

RESULTS

Of the 829 participants, 57% were female and the mean age was

75 years (sd = 9 years). Three percent were single, 60% married orpartnered, 5% divorced or separated and 32% were widowed.

Nineteen percent had completed primary school, 39% high school,

16% held a trade certificate and 26% a diploma or degree. Thirty-

four percent were living at home, 52% were living at home with

support (by their family or carer) and 14% were in residential

accommodation (in residential care, hostel or nursing home). Twen-

ty-two percent were working, 75% were retired or were the home-

maker and 4% were unable to work because of illness or disability.Five percent were in excellent health, 19% in very good health,

31% in good health, 29% in fair health and 16% in poor health. The

mean SF-12 MCS was 51.79 (sd = 9.75) suggesting participants were

in good mental health, and for the PCS it was 43.40 (sd=10.43)

which suggested fair physical health. Regarding quality of life, for the

WHOQOL-Bre` f Physical domain the mean was 65.98 (sd=18.09),

for the Psychological domain it was 66.89 (sd=14.33), for the Social

domain it was 68.55 (sd=18.15) and for the Environment domain itwas 73.50 (sd=13.05). The mean AQoL utility score was 0.64

(sd=0.26). For both the WHOQOL-Bre` f and AQoL, the scores were

below population norms, suggesting a limited quality of life (Haw-

thorne et al. in press; Hawthorne and Osborne, 2005).

For the construction sample, the PCA results showed that six of

the seven items formed a unidimensional scale with mean loadings

between 0.63 and 0.84. The mean for the seventh item (Item 5: Others

felt they had to help me) was 0.34. The IRTCs showed a similarpattern, as shown in Table 1. These results indicated this item was

not substantially contributing, so it was deleted. Following deletion,

the Cronbach a was 0.81 for the remaining 6 items compared with

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0.76 for all 7 items. The 6 remaining items were numbered 16 for

convenience.

These 6 items were examined using the validation sample. TheSEM model is presented in Figure 1, which indicates the items

formed a robust model with excellent statistical properties.

Partial credit IRT ascertained the order in which social losses are

endorsed (IRT model statistics: v2 for parameter equality = 363.69,

p < 0.01, Separation reliability = 0.99). The difficulty estimates ex-

pressed in logits were: Item 1: )0.24 (weighted T = 0.1); Item 2:

)0.34 ()4.8); Item 3: 0.97 (3.4); Item 4: 0.22 (0.9); Item 5: )0.07

()

2.7), and Item 6:)

0.61 (constrained item).Using all cases in the study, the Spearman correlations between

items ranged from 0.29 (items 1 and 5) to 0.59 (items 2 and 6). The

distribution of FS scores is presented in Figure 2. This shows that

50% of participants obtained scores in the range 2024, indicating

that they were not socially isolated. Other participants were spread

over the FS range. For the 6 FS items, Cronbach a = 0.83.

The FS was correlated with the SF-12 MCS and PCS scales, the

WHOQOL-Bre` f domains and AQoL dimensions (Table II). The FSwas significantly more correlated with the SF-12 MCS when com-

pared with the PCS (Cohens q = 0.18, p < 0.01). For the WHO-

QOL-Bre` f, the highest correlation was with the Psychological domain

when compared with the Physical and Environment domains

(q = 0.17 and 0.11, p < 0.05, respectively). There were no other

significant differences. For the AQoL, the highest correlation was

with the Social Relationship dimension (q = 0.49 for Illness, 0.41 for

Independent Living, 0.44 for Physical Senses and 0.32 for Psycho-logical Wellbeing,p < 0.01 for all). Psychological Wellbeing was also

more highly correlated with the FS than Illness (q = 0.16, p < 0.01)

or Physical Senses (q = 0.12, p = 0.05).

Table III presents discriminatory tests of the FS by correlates of so-

cial isolation: accommodation, work status, community involvement,

wellbeing, marital status, and depression. As shown, on all measures the

FS discriminated as expected. Although not reported in the table, for

those living in a nursing ward (n = 5) the mean FS score was 12.22,suggesting a high level of social isolation. The table also includes an

analysis by study cohort, showing there were significant differences,

although the OUT and MAR cohorts obtained very similar scores.



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FS scores can be categorised into five levels. Those who are very

socially isolated will obtain scores in the range 011 because they will

have endorsed at least 1 item at level 1 or lower (i.e. have reported anisolating condition most of the time or almost always). Isolated

or low level social support respondents are those with scores of 12

15, which require endorsement of at least two items at or lower than

level 2. Some social support refers to the range 1618, because in this

range at least two items at level 3 or lower must be endorsed. The

socially connected range is between 1921 because at least one item at

level 3 or lower must be endorsed. The very socially connected will

score within the range 2224. This requires endorsement of at least

four items at level 4. A person obtaining a score in this range cannot

have endorsed any item at levels 0 or 1.

Based on this classification, 4% of the sample obtained scores

indicating they were socially isolated, 11% were isolated with low

TABLE I

Scale analysis of the Friendship Scale item pool: results of 20 random

iterations (50% of construction cases)

Items EFA (Principal

component)

Reliability analysis

(IRTCa)

Mean 95% CIs Mean 95% CIs

1 It has been easy to

relate to others0.64 (0.620.66) 0.50 (0.480.52)

2 I felt isolated from

other people

0.81 (0.800.81) 0.66 (0.640.67)

3 I had someone

to share my feelings with0.64 (0.630.66) 0.48 (0.460.49)

4 I found it easy to get in

touch with others when

I needed to

0.72 (0.710.74) 0.56 (0.550.58)

Others felt they had

to help me0.34 (0.320.37) 0.23 (0.210.25)

5 When with other people

I felt separate from them0.74 (0.730.76) 0.57 (0.550.59)

6 I felt alone and friendless 0.83 (0.820.84) 0.67 (0.660.69)

Eigenvalue 3.36 (3.303.42)

% Variance 64.53 (63.7165.34)

Cronbach a 0.76 (0.750.77)

aItem-rest-of-test correlation.

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support, 17% had some support, 28% were socially connected and40% were very socially connected. Using this scheme, for example,

those who were single, separated, divorced or widowed (n = 326)

were twice as likely as those who were partnered (n = 480) to report

they were socially isolated or had low social support (OR: 2.16; 95%

CI: 1.443.25).

SocialIsolation

Easy to relate to others

Isolated from others

Someone to share with

Easy to get in touch

Felt separate from others

Alone and friendless

E1

E2

E3

E4

E5

E6

0.60

0.83

0.50

0.56

0.73

0.78

0.36

0.69

0.25

0.31

0.53

0.60

0.23

0.34

Figure 1. Structural equation model of the Friendship Scale items, based on

validation cohort.

Model shows standardised regression weights.

Statistics: N= 374, model = ADF, v2 = 8.18, df = 7, p= 0.32,

CFI = 0.99, RMSEA = 0.02 (95% CI: 0.000.07).

Friendship Scale

24.022.020.018.016.014.012.010.08.06.04.02.00.0

Frequency

250

200

150

100

50

0

Figure 2. Distribution of FS scores (n = 816).



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DISCUSSION

Although there are many scales measuring social isolation, in general

these are long stand alone instruments for interview settings, short

instruments with items that are negatively worded, or they are

embedded within longer instruments. Because of their length longer

instruments are not particularly suitable for use in instrument bat-teries, while short negative scales may invoke response resistance or

denial. This paper describes the development of the FS, which was

designed to overcome these limitations through measuring perceived

social isolation.

Analysis of the item pool suggested that 6 of the 7 items formed a

unidimensional scale. The 7th item measured a different construct

and was removed; a step which improved scale reliability.

The PCA proportion of explained variance was 65%. It is ac-

cepted that the proportion of explained variance should be in the

vicinity of 75% for scale items to satisfactorily explain a latent con-

cept (Pedhazur and Schmelkin, 1991; Streiner and Norman, 1995).

The PCA analysis, however, may be misleading because the Pearson

TABLE II

Concurrent validation with the SF-12, WHOQOL-Bre` f and AQoL scales

Friendship scale

N rs

SF-12 Physical (PCS) 808 0.21*

Mental (MCS) 808 0.37*

WHOQOL-Bref Physical 808 0.34*

Psychological 811 0.48*

Social 798 0.44*

Environment 811 0.39*AQoL Medication use 784 0.22*

Independent living 784 0.29*

Social relationships 794 0.61*

Physical senses 802 0.26*

Psychological

wellbeing

802 0.37*

AQoL utility 771 0.53*

*p < 0.01.

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TABLEIII

FSscoresbycorrelateso

fsocialisolation

N

Friendship

Scale

scores

Statisticsa

Mean

sd

Accommodation

Athome,supported

399

20.27

3.93

Athome,un

supported

264

19.47

3.99

Family,sheltered

housingorcommunity

care

30

18.60

3.61

Residentialc

are/

Nursinghom

e

79

17.22

4.49

F=

15.47,df=

3,768,p

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