Developing and validating a measure of community capacity: Why volunteers make the best neighbours

Accepted Manuscript Developing and validating a measure of community capacity: Why volunteers make the best neighbours Sarah A. Lovell, Andrew R. Gray, Sara E. Boucher PII:

S0277-9536(14)00616-9

DOI:

10.1016/j.socscimed.2014.09.049

Reference:

SSM 9719

To appear in:

Social Science & Medicine

Received Date: 26 February 2014 Revised Date:

7 August 2014

Accepted Date: 24 September 2014

Please cite this article as: Lovell, S.A., Gray, A.R., Boucher, S.E., Developing and validating a measure of community capacity: Why volunteers make the best neighbours, Social Science & Medicine (2014), doi: 10.1016/j.socscimed.2014.09.049. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT Social Science and Medicine manuscript #: SSM-D-14-00673 Title: Developing and validating a measure of community capacity: Why volunteers make

RI PT

the best neighbours

SC

Authors:

Andrew R. Gray2 Sara E. Boucher2 University of Canterbury

2

University of Otago

AC C

Sarah Lovell

EP

Corresponding author:

TE D

1

M AN U

Sarah A. Lovell1

School of Health Sciences, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand. Email: [email protected]

ACCEPTED MANUSCRIPT Abstract Social support and community connectedness are key determinants of both mental and physical wellbeing. While social capital has been used to indicate the instrumental value of

RI PT

these social relationships, its broad and often competing definitions have hindered practical applications of the concept. Within the health promotion field, the related concept of

community capacity, the ability of a group to identify and act on problems, has gained

prominence (Labonte & Laverack, 2001). The goal of this study was to develop and validate

SC

a scale measuring community capacity including exploring its associations with socio-

M AN U

demographic and civic behaviour variables among the residents of four small (populations 1,500–2,000) high-deprivation towns in southern New Zealand. The full (41-item) scale was found to have strong internal consistency (Cronbach’s alpha=0.89) but a process of reducing the scale resulted in a shorter 26-item instrument with similar internal consistency (alpha 0.88). Subscales of the reduced instrument displayed at least marginally acceptable levels of

TE D

internal consistency (0.62–0.77). Using linear regression models, differences in community capacity scores were found for selected criterion, namely time spent living in the location,

EP

local voting, and volunteering behaviour, although the first of these was no longer statistically significant in an adjusted model with potential confounders including age, sex,

AC C

ethnicity, education, marital status, employment, household income, and religious beliefs. This provides support for the scale’s concurrent validity. Differences were present between the four towns in unadjusted models and remained statistically significant in adjusted models (including variables mentioned above) suggesting, crucially, that even when such factors are accounted for, perceptions of one’s community may still depend on place. Key words: New Zealand, community capacity, place effects, volunteering

1

ACCEPTED MANUSCRIPT Introduction Strong communities possess the skills, resources, and networks to advocate effectively for services, are better prepared to respond to disasters and other uncertainties,

RI PT

and possess the capacity to absorb resulting change (Magis, 2010; Veenstra, 2002). Social support and community connectedness are key determinants of both mental and physical wellbeing (Kawachi et al., 2004; Szreter & Woolcock, 2004), and many researchers have applied the concept of social capital to gain insight into the nature of collective social

SC

relationships. Yet, the application of social capital to community development has been

M AN U

hindered by broad definitions that have variously emphasised the nature of social networks (hierarchical or linear), the norms (such as trust) which lubricate cooperation between community members, or the resources that travel through such networks (see Lovell, 2009). Reflecting this broad scope, measures of social capital include a range of, often controversial, indicators such as the number of people who are members of a voluntary organisation and

TE D

levels of trust in one’s government (Capriano & Fitterer, 2014; Putnam, 2000). Theories of social capital have still to shed light on how we might enhance the collective efficacy of

EP

communities.

Community capacity, namely the ability (skills, resources, and networks) of a group

AC C

to identify and act on problems (see Labonte & Laverack, 2001), has gained prominence as a prerequisite for successful health promotion programmes and as a critical component of resilience in the disaster planning and environmental literature (Hawe et al., 1997; Magis, 2010). The term community capacity, as recently added to the WHO Health Promotion Glossary, is informed by concepts such as community empowerment and competence (Goodman et al., 1998; Smith, Tang & Nutbeam, 2006). Health promoters have sought to build community capacity as a ‘parallel track’ to the programmes they implement, recognising the approach will empower the communities they work with and encourage 2

ACCEPTED MANUSCRIPT support and buy-in beyond the funded life of a programme (Hawe et al., 1998). The strengthbased approach enables communities to identify and build on their collective assets. Despite their current popularity, the merit of such asset-based approaches remains largely untested (Friedli, 2013). As a result, the benefits of building community capacity are not always

RI PT

recognised and health promoters have reported undertaking this work covertly due to lack of support or scope for it within their formal contracts (Hawe et al., 1997).

The first goal of our research was to develop, both theoretically and empirically, a

SC

scale to measure community capacity and establish its face, content, and construct validity.

M AN U

The second goal was to explore predictors of community capacity scores, which would be of interest in themselves as well as allowing some evaluation of the criterion (concurrent) validity of the scale. The setting was four small (populations of between 1,500 and 2,000) high-deprivation towns in southern New Zealand (Mataura, Milton, Riverton, and Winton). In this paper, we discuss the history and nature of community capacity as a construct, outline

TE D

the dimensions of our scale, and develop a series of items before examining differences in the resulting scores between the communities. In our discussion, we interrogate the nature and

EP

reasons for the observed place effects on community capacity amongst those locations. Finally, we reflect on interventions that may lead community capacity to be built or eroded.

AC C

The importance of strong communities Until recent decades, understandings of ‘community’ were based on a geographically

defined area and assumed commonalities amongst people residing within those places (Woelk, 1982). Changing lifestyles (including long commutes), new technology (such as the television) and growing inequalities have restricted the time and money individuals in the US have to engage civically in their local communities (Putnam, 2000). Yet, research into neighbourhood effects continues to suggest there is something about the geographical places

3

ACCEPTED MANUSCRIPT that we live that has the potential to shape our health and wellbeing (Poortinga, 2012). Thus, we adopt an understanding of community that is grounded in physical co-location to explore what ‘being together’ means in New Zealand small towns. A consequence of our focus on small towns is that we need not contend with the difficulties urban research has faced

RI PT

reconciling administrative ‘neighbourhood’ units with lived neighbourhood (Flowerdew, Manley & Sabel, 2008).

Communities offer a mediating force linking the micro level of the individual and the

SC

macro economic, political and cultural structures that shape society (Robertson & Minkler, 2004). As a consequence, communities can be protective and reduce the impact that poverty,

M AN U

institutional racism and other sources of structural disadvantage may have. Strong communities (often characterised as cohesive and high in social capital or community capacity) can be more effective proponents than individuals in preventing the erosion of existing services due to the skills, resources, and networks they possess and can leverage in

TE D

times of need (Veenstra, 2002). This scenario has been well-documented in rural communities where long-term population decline led the state to withdraw services closing schools and hospitals and triggering local activism in response (Barnett & Barnett, 2003;

EP

Kearns et al., 2009). In communities that lack capacity, members are less likely to discuss

AC C

challenges with their neighbours or mobilise the skills and resources they possess to address the needs of their community. Often, it has been observed, it takes a crisis for a community to acknowledge a problem and take action (Labonte, 1994; Lovell et al., 2011). In this way, community capacity—like social capital—has the potential to bring benefit to some communities, sometimes at the expense of other, less organised, communities. Very little quantitative research has been undertaken to examine the benefits of building community capacity on collective wellbeing; a notable exception being work undertaken by Jung & Viswanath (2013) who examined the relationship between community 4

ACCEPTED MANUSCRIPT capacity and health status amongst neighbourhoods within a district of Seoul, South Korea. They found that lower community capacity was associated with collectively worse health status amongst residents. Despite the paucity of research on community capacity, similar constructs provide us with evidence of its potential value. For example, Sampson et al.,

RI PT

(1997) found collective efficacy was associated with lower levels of violence within

neighbourhoods and personal victimization. Likewise, Poortinga (2012) found both social cohesion and civic participation were positively associated with community health outcomes

SC

but did not act as a buffer for the effects of neighbourhood deprivation. At an individual

level, a sense of belonging to a community is important to wellbeing and a higher number of

M AN U

health symptoms have been identified amongst those who report not feeling that they are a part of their community (Veenstra, 2001). Meanwhile, indicators of lower neighbourhood cohesion have been correlated with worse mental health outcomes (Ivory et al., 2011). When we turn to explore ‘place’ effects on health, the evidence is less consistent;

TE D

McIntyre, Ellaway and Cummings (2002, p.128) explain that while there may be no “one single, universal ‘area effect on health’ there appear to be some area effects on some health

EP

outcomes, in some population groups, and in some types of areas.” On the other hand, Doran, Drever and Whitehead (2005) found disparities in health outcomes between locations that

AC C

cannot be explained by material deprivation and composition alone and the reasons for these disparities continue to be debated. However, the literature on neighbourhood effects indicates that individuals within a community tend to behave and hold values that share more in common with their neighbours than what we might expect from their demographic characteristics (Johnston et al., 2005). This suggests there is an element of being together, or social interaction, that shapes attitudes and beliefs. Critics have been cautious in advocating for the widespread adoption of capacity building strategies, in part, because the long time-frame required to achieve improvements to health 5

ACCEPTED MANUSCRIPT outcomes has limited the availability of strong evidence of its effectiveness (Mansuri & Rao, 2004; Roussos and Fawcett, 2000). Our work contributes to the sparse body of empirical literature on community capacity building by interrogating the nature of the concept and its predictors. In doing so, we hope to draw attention to a concept that is already in wide use

RI PT

within the field of health promotion (Lovell et al., 2011). Dimensions of community capacity

SC

The vast majority of studies seeking to assess community capacity have drawn on the views of experts to characterise the nature of social relationships and factors that encourage

M AN U

action within a community (e.g. Beckley et al., 2008; Gibbon et al., 2002; Goodman et al., 1998; Jackson et al., 2003). Such expert-informed approaches allow for in-depth understanding of the nature and roles of external agencies, the resources and financial support available within a community, and they enable rapid evaluation of progress on community

TE D

development initiatives (Maclellan-Wright, et al., 2007). However, existing instruments are applicable to an organisational, rather than a population, context (for example, Chinman et al., 2005; Laverack, 2005; Lempa et al., 2006) and provide limited insight into social

EP

relations, connections to place, or perceptions of democratic processes amongst the wider community. In this paper, we contribute to the existing literature with the development of a

AC C

quantitative tool to measure capacity on a community-wide scale. Developing a generaliseable and standard measure of community capacity at the

ecological level remains a challenge. Ecological measures, such as counting the number of agencies involved in a community, have been criticised in the social capital literature for failing to capture the dynamics of community engagement (Subramanian et al., 2003). In contrast, population-based surveys allow us to explore whether relationships are consistent at the individual and collective (community) level thus we can capture the otherwise elusive

6

ACCEPTED MANUSCRIPT ‘social dynamism’ of communities (Kawachi, 2004) and understand of how we may best target initiatives. Community capacity, like sense of community (see Peterson et al., 2008) and social

RI PT

capital, is a multi-dimensional construct. We undertook a review of the health promotion literature and found five dimensions of community capacity were consistently prominent: leadership, resources, problem assessment, connections & networks, and community attitudes and these formed the basis of our instrument development (Beckley et al., 2008; Gibbon et

SC

al., 2002; Goodman et al., 1998; Jackson et al., 2003). A subsequently published literature

M AN U

review by Liberato et al. (2014) supports our work identifying seven similar constructs (leadership, resource mobilization, participatory decision-making, partnership/linking/networking, sense of community, learning opportunities and skills development, and development pathway) as the most widely accepted domains of community capacity these were largely consistent with our final instrument. The above domains contrast

TE D

markedly with the concept of community capacity that underpins Jung and Rhee’s (2013) work. Jung and Rhee (2013) have developed the only population-level instrument to measure

EP

community capacity that we are aware of, however, the subscales (comprising of social trust, social cohesion, community participation, social networks and community identity)

AC C

conceptually align the instrument very closely with social capital and overlook some critical components of community capacity. Specifically, the domain of ‘leadership’, which was the most significant component of community capacity in a large organisational study (Lempa et al., 2006), is not addressed, nor is ‘problem assessment’ which conceptually is at the crux of community capacity (a community’s ability to identify problems within their community and work together to resolve them).

7

ACCEPTED MANUSCRIPT Methods Survey Instrument Dimensions (subscales) of the community capacity scale were informed by the

RI PT

literature (discussed above) and verified by key informant interviews in one of the study sites. Interview participants noted the importance of connections to their town and we added the dimension ‘sense of place’ in response. This was a point of difference from previous studies

SC

but consistent with Jung and Rhee’s (2013) ‘community identity’ dimension of community capacity.

M AN U

Once the dimensions of community capacity were established we sought to identify survey items that would capture the qualities of each. Due to a lack of quantitative measures of community capacity we drew on previous qualitative research and a review of scales assessing similar concepts (e.g. social capital, resilience, social cohesion) to inform our item

TE D

development. Existing scales in their entirety were deemed unsuitable for assessing the dimensions of community capacity (see Table One) and instead we drew upon items from these existing scales and developed new items also informed by analysis of the qualitative

EP

interviews. The initial 41-item community capacity instrument was reduced to 26 items in

AC C

order to minimise respondent burden for future applications of the scale. We had initially identified ‘resources’ as a dimension of community capacity but this subscale was removed due to lack of internal consistency and participant difficulty assessing the nature of their community’s resources. The six survey dimensions that made up the final table are described in Table One. The resulting instrument consisted of a series of seven-point Likert-type items for respondents to indicate their level of agreement or disagreement with a statement and questions on demographics (including age, sex, ethnicity, religious beliefs, and time spent in

8

ACCEPTED MANUSCRIPT the community) and civic behaviours (e.g. Have you volunteered in the last six months? Did you vote in the last local election?). [Insert Table 1 roughly here]

RI PT

Data Collection This is a secondary analysis of data collected for a planned intervention and so sample size calculations were not based on the analyses presented here. We wanted to be able to

SC

estimate mean scores with 95% confidence interval half-widths of 0.15 standard deviations for each of two roughly equally-sized groups (Mataura and the other communities who would

M AN U

have acted as the control group), and to have 80% power to detect differences between these two groups of 0.3 standard deviations using two-sided tests at the 0.05 level. Both calculations indicated that we required 180 respondents with complete data in each group (360 overall) and so assuming a 60% response rate, 300 residents needed to be approached in

TE D

each group (600 overall). In evaluating the sample’s adequacy for the present analyses, we considered the robustness of Cronbach alpha estimates. Yurdugül (2008) suggests the sample size required for estimating Cronbach’s alpha depends on the first eigenvalue from a

EP

principal components analysis (PCA). As the first eigenvalue from PCA using polychoric

AC C

correlations obtained from the 267 observations with complete data was 6.95, sample sizes of n=30 or greater can be regarded as robust. For the first group, a sample of 303 Mataura residents (including those Māori, the

indigenous population of New Zealand, who opted to register for their Māori electorate) was randomly selected from the electoral roll in October 2011. To enhance representativeness, a stratified sample using age group, sex, and NZ Deprivation Quintile (a geographic measure of socio-economic status) was used. A door-to-door survey took place in October and November of 2011. Each selected individual was visited up to three times, on different days 9

ACCEPTED MANUSCRIPT and at different times of day. If, following three attempts, the person had not been contacted, a pre-paid postal survey was left in their mailbox. After removing addresses that were incorrect or out of date, a response rate of 58% (145 surveys) was achieved. Mataura was to be the focus of an intervention, which was not ultimately implemented. As such, a control

RI PT

group was recruited at the same time. This comparison sample consisted of the same number of residents from three small South Island towns that were considered to be comparable to Mataura (Milton, Riverton and Winton). These residents were matched demographically

SC

(using age groups, sex and New Zealand Deprivation Index quintiles) with the Mataura study sample. A 54% response rate was gained from the postal survey of the comparison towns.

M AN U

Postal surveys were followed up with a postcard one week later and a second survey to nonresponders three weeks after the first survey was sent. Of the comparison sample, 51 individuals were no longer living at the address listed on the electoral roll, bringing our total number of potential participants down to 249 individuals. Amongst the 104 non-responders,

TE D

43 declined to participate and 61 postal surveys were not returned. Surveys were scanned electronically with automatic detection of respondent answers.

EP

Subsequent manual checks were undertaken to ensure the accuracy of the automated data entry. Data was cleaned and recoded using the software SPSS (Statistical Package for the

AC C

Social Sciences) and data analysis undertaken by the second author using the software programme Stata version 13.1. For the combined sample, the completion rate for individual items in the scale was very high, ranging from 97-100%. Missing data for other variables was generally low (with the highest percentage being 17% for household income). Analysis Counts and percentages were provided to describe the sample in terms of variables of interest and to allow comparisons with census data where available. The initial subscales,

10

ACCEPTED MANUSCRIPT developed to have face and content validity, were refined by examining changes in Cronbach alphas by removing or adding items to particular subscales in ways that maintained a coherent theoretical model but also allowed for re-examination of how respondents might interpret questions. Once the subscales were finalised, the scale was validated in terms of

RI PT

associations with anticipated predictors of community capacity (time spent living in location, local voting behaviour and volunteering) in unadjusted and adjusted linear regression models. Where responses were missing for some community capacity items, imputed total and

SC

subscale scores were calculated based on mean scores to answered items (provided at least 80% of relevant items had responses). Other variables included in the regression models as

M AN U

variables of interest or potential confounders were location, sex, age group (18–30, 31–40, 41–50, 51–70, 71+), prioritised ethnicity (a respondent indicating that they identified as Māori was coded as such irrespective of their own responses; a respondent indicating an ethnic identity other than Māori or NZ/European was coded as “other”, leaving the remainder

TE D

as NZ/European), marital status (single, married, separated), education (primary school, secondary school, post-secondary, university), employment (full-time, part-time, retired, student/unemployed, and on sick leave), household income (NZ$ 0–20,000; 20,001–30,000;

EP

30,001–50,000; 50,001–70,000; 70,001–100,000), religious beliefs (Christian, other/none),

AC C

and national voting (yes, no). These categories used in the regression models were based on combining available categories (as shown in the sample descriptives) so as to achieve at least ten respondents in each. Variables with unadjusted p<0.20 were included in the adjusted model. Standard model diagnostics were used (including histograms to assess normality and scatter plots to assess homoscedasticity of residuals). Variance inflation factors were checked for all regression models with values greater than 5 considered worthy of further attention. All statistical tests were performed at the two-sided 0.05 level and no adjustments for

11

ACCEPTED MANUSCRIPT multiple comparisons were made. Where 0.05
RI PT

The survey sample was comparable to the most recent 2006 New Zealand Census population in terms of sex and ethnicity (see Table 2). There were small differences in the age brackets used in our survey and the Census with those aged under 30 slightly

SC

underrepresented in our sample along with Māori residents of the towns, while we were

slightly overrepresented in terms of those with higher educational qualifications (see Table

M AN U

2). Most respondents (75%) were educated to a primary or secondary school level and 58% received a household income of $50,000 per year, or less (lower than the median household income for the whole of New Zealand that year of $62,853).

TE D

[Insert Table 2 roughly here]

Instrument internal consistency

The initial scale with 41 items had a Cronbach’s alpha coefficient of 0.89 indicating

EP

good internal consistency and this was evident over all four communities (alphas ranged between 0.87 and 0.91). At this stage, opportunities to reduce the instrument in order to

AC C

minimise respondent burden or enhance validity were investigated. Items whose removal would meaningfully improve internal consistency as measured by Cronbach’s alpha were identified and re-evaluated. The weakest subscale (resources, alpha 0.55) was removed at the same time. All items were re-evaluated for validity by the author (SL) involved in interviewing Mataura key informants. This allowed us to reduce the instrument to a much shorter 26 items with comparable overall internal consistency (alpha 0.88). The results

12

ACCEPTED MANUSCRIPT presented here are based on those from the short instrument, the items of which are listed in Table 2 and shown in Appendix A. [Insert Table 3 roughly here]

RI PT

The correlations between the total scale and subscales are shown in Table 3. All subscales displayed at least a moderate subscale-scale correlation with the total score (0.58– 0.82) and still a moderate subscale-rest of scale correlation where that particular subscale was

SC

excluded from the calculation (0.42–0.70). Correlations between subscales ranged between 0.24 and 0.55. This suggests that there is a common factor underlying all subscales but also

[Insert Table 4 roughly here]

M AN U

that they capture partially distinct aspects of that factor.

Validation of community capacity through examining associations with criterion

TE D

variables

Community capacity scores differed between locations (overall p=0.021) with the highest scores in Winton (mean 137.0, standard deviation 2.6), Riverton (131.2, 3.3), Mataura

EP

(131.1, 1.5), and then Milton (126.0, 2.2). Unadjusted models found a non-linear association with time lived in their location (overall p=0.001) with higher community capacity among

AC C

those who had lived there for 21+ years compared to 1–5 and 6–15 years. These differences were statistically significant. Interestingly, those who had lived in a town for less than 1 year had a similar (high) mean community capacity score to those residents of 21+ years but differences between this small group and longer-term residents were not statistically significant (see Table 4). Higher community capacity scores were also noted for those who were older (overall p<0.001) identified as New Zealand/European ethnicity (overall p=0.021, with a statistically significant difference between NZ/European and other), identified as

13

ACCEPTED MANUSCRIPT belonging to a Christian religion (p<0.001), had voted in the last local election (p<0.001), had voted in the last national election (p=0.023), or who had volunteered in the past six months (p<0.001). The associations with two of the criterion variables (voting in the last local

RI PT

election and volunteering) were as expected. Those variables significant at the p<0.20 level in the unadjusted model, that is, those listed above along with income (overall p=0.100) were included in the adjusted model (see Table 5). This model explained 31.0% of the variation in scores, with an adjusted R-squared

SC

value of 0.234. Location remained a statistically significant predictor of community capacity

M AN U

after adjusting for these variables (overall p<0.001). Only two other associations remained statistically significant, namely higher scores for voters in the last local election (p=0.008) and volunteers (p<0.001). The time lived in the location was no longer statistically significant, although there was a tendency for a pattern of higher scores among those who had lived there longer (p=0.075). These findings indicated the importance of community context

those communities.

TE D

in shaping the perceptions of community members beyond the characteristics of people in

AC C

EP

[Insert Table 5 roughly here]

Discussion

Study communities included four small, low SES towns in the South Island of New

Zealand selected for their relative homogeneity in size and average income. Differences in community capacity scores were present between towns and remained statistically significant in adjusted models that included a range of plausible confounders (age, years living in community, sex, ethnicity, education, marital status, employment, household income,

14

ACCEPTED MANUSCRIPT religious beliefs, voting behaviour, and volunteering) suggesting, crucially, that even when such factors are accounted for, perceptions of one’s community may still depend on place. Finding differences in community capacity between places that cannot be explained

RI PT

by the composition of the population suggests that a collective approach (rather than individually focused) may be an effective means of boosting community capacity.

Alternatively, the differences between towns could be due to residual confounding but we are unable to suggest sufficiently influential variables that might account for this. While this

SC

study was undertaken in small high-deprivation towns in New Zealand we suggest the

M AN U

instrument is transferable to other countries and settings. The study’s understanding of community capacity draws on key work undertaken in developing country settings (see Laverack, 2005), however, considerable testing of the instrument would be necessary to assess the cultural transferability of the items. We hope to test the instrument in urban settings in New Zealand in the near future and anticipate that overall community capacity

TE D

scores will be weaker due to social changes that have reshaped the geographies of social networks (Putnam, 2000). Specifically, technological developments have made it easier to

EP

socialise with individuals outside of one’s immediate neighbourhood potentially weakening the community ties that underpin community capacity.

AC C

Previous research into community capacity has been largely qualitative in nature,

drawing on the views of community experts identified through their heavy community participation in a volunteer and/or paid capacity. To assess whether our population-based measure of community capacity might differ from one informed by community experts, we examined relationships between community capacity with measures of civic behaviour. We asked participants whether they had carried out several civic behaviours (voted in the last local election, voted in the last national election, and volunteered in the past six months). Voting in the last local election and having volunteered in the last six months were the only 15

ACCEPTED MANUSCRIPT variables (aside from place) that were found to be statistically significant predictors of higher community capacity in the adjusted model. Overall, fifty-four percent of respondents reported volunteering in the past six months and these individuals perceived their community to have higher capacity than non-volunteers. These findings indicate that ‘lay’ and expert

RI PT

(civic-minded) experiences of community capacity differ providing support for a communitylevel survey of community capacity. Similar differences in survey responses were evident between leaders and participants of public health community initiatives studied by Lempa et

SC

al., (2006) leading the authors to develop unique scales for the two groups. Higher rankings

providing additional criterion validity.

M AN U

community capacity scoring by volunteers in our study followed the anticipated association,

While individual volunteers in our study rated their town as having higher community capacity, at the community level, towns with high levels of volunteers did not have higher mean community capacity scores. Milton had the highest rate of volunteering amongst all

TE D

four communities, but lowest levels of community capacity. Mataura, in contrast, had the lowest rates of volunteering and was the third ranking town in community capacity scores.

EP

Amongst the explanations for this seeming paradox are the possibilities that people volunteer when they recognise a need in their community, or alternatively, volunteering leads people to

AC C

rank their community’s capacity higher. Volunteering appears to have psycho-social benefits, evident in the volunteer’s more positive views of their community. While investing in volunteering may be a means of building community capacity, it appears a very high critical mass of volunteers would be required to improve the relative standing of a community with low capacity. Interested in possible interventions to build community capacity, we examined other characteristics that might influence the nature of a community, specifically, economic context and residential tenure. We found no clear and interpretable association between economic 16

ACCEPTED MANUSCRIPT opportunities and community capacity in the survey results, specifically, income was not a statistically significant predictor of community capacity at the individual level and no clear relationship was evident at the town scale. Instead, we turned to the literature identifying housing tenure as strong ties and longevity within a community may be important in

RI PT

determining commitment and involvement in that place. In our study, Milton, with the lowest community capacity scores, had 61.6 percent of the population living in dwellings they

owned. This rose to 67.2 percent in Mataura, 77.0 percent in Riverton, and 79.2 percent in

SC

Winton, following the exact same pattern as community capacity scores. While this

observation is based on data from only four towns, and further research is clearly needed,

M AN U

within our study this provides further insight into place differences in community capacity that we were not otherwise able to explain. In the most recent iteration of the survey we have asked about housing tenure and hope to undertake this analysis in future. Concern regarding the possibility of ecological fallacy and conceptual distinction from ‘sense of place’, have

TE D

prevented analysis at this stage. Interestingly, household tenure is a commonly used, and effective, indicator of disadvantage in the UK (where Census data does not collect income information) as it is often the largest household expense and/or asset (McIntyre, Ellaway &

EP

Cummings, 2002; Galobardes et al., 2006).

AC C

Strengths of our study include the careful development of the instrument informed by a robust body of literature identifying the domains of community capacity and key informant interviews. We benefited from key stakeholder involvement in Mataura from the planned intervention. Limitations include the response rate and possible biases from underrepresentations of young and Māori residents, and over representation of more educated residents. We anticipated volunteers and other civically active individuals would be more likely to complete a survey eliciting their perceptions of their community. However, the response rate is comparable to other New Zealand studies and as the focus of this paper is on 17

ACCEPTED MANUSCRIPT associations rather than estimation, we do not feel it likely that associations found would differ meaningfully in non-respondents. Conclusions

RI PT

Through the development of a population-based survey instrument, we have begun to disentangle individual and collective influences on community capacity. Our study has

produced several empirical results. First, an instrument with adequate face, content, and

SC

construct validity has been created and plausible associations found with socio-demographic and behavioural predictors. The residual differences in community capacity between the

M AN U

towns suggests that contextual influences, that is, their material and collective features influence community capacity to a much greater degree than might be expected given the composition of the communities thus supporting the presence of ‘place effects’. Second, these results suggest non-expert perceptions of community capacity offer a viable and

TE D

comparable measure of community capacity between locations, comparisons between places and investigating changes over time. Civic behaviours were statistically significant predictors of community capacity in the adjusted model suggesting a population-based measure may be

EP

a more accurate indicator of a community’s capacity to resolve challenges than expertinformed opinions. Follow-up over time will be necessary to examine whether this is the

AC C

case. The paradoxical finding that high numbers of volunteers within a community was not a predictor of high community capacity highlights the complexity of community dynamics Observations of a community’s capacity (based, for example, on the number of

resources secured) face similar limitations to the measurement of social capital, often being context and culture-specific (Surbramanian, Lochner & Kawachi, 2003). Our instrument has been applied only in the context of New Zealand small towns and further study is needed to assess its transferability to international and urban contexts.

18

ACCEPTED MANUSCRIPT The results of our study support the suggestion that strong communities may offer a buffer against sources of structural disadvantage, such as poverty. Our findings suggest that structural interventions may be an effective means of building community capacity in small towns. Initiatives to build permanent employment opportunities may encourage longer tenure

RI PT

within a community, which is positively associated with community capacity. Likewise,

mechanisms (such as financial support) to encourage home ownership may have benefits for community capacity as residents build deeper and longer-term connections with their

SC

neighbours). Our follow-up study, currently underway, asks participants about their housing

AC C

EP

TE D

M AN U

tenure and will enable us to undertake further analysis of this possible predictor.

19

ACCEPTED MANUSCRIPT References Barnett, R., & Barnett, P. (2003). “If you want to sit on your butts you’ll get nothing!” Community activism in response to threats of rural hospital closure in southern New Zealand.

RI PT

Health & Place, 9(2), 59-71. Beckley, T., Martz, D., Nadeau, S., Wall, E., & Reimer, B. (2008). Multiple Capacities,

Multiple Outcomes: Digging Deeper into the Meaning of Community Capacity. Journal of

SC

Rural and Community Development, 3(3), 56-75.

Carpiano, R., & Fitterer, L. (2014). Questions of Trust in Health Research on Social Capital:

M AN U

What aspects of personal network social capital do they measure. Social Science & Medicine, 116, 225-34.

Chinman, M., Hannah, G., Wandersman, A., Ebener, P., Hunter, S., Imm, P., & Sheldon, J. (2005). Developing a Community Science Research Agenda for Building Community

TE D

Capacity for Effective Preventive Interventions. American Journal of Community Psychology, 35(3/4), 143-57.

Doran, T., Drever, F., & Whitehead, M. (2005). Health Underachievement and

EP

Overachievement in English Local Authorities. Journal of Epidemiology and Community

AC C

Health, 60, 686-93.

Flowerdew, R. Manley, D., & Sabel, C. (2008). Neigbourhood Effects on Health: Does it matter where you draw the boundaries? Social Science & Medicine, 66(6), 1241-55. Friedl, L. (2013). ‘What We’ve Tried, Hasn’t Worked’: The politics of assests based public health. Critical Public Health, 23(2), 131-45. Galobardes, B., Shaw, M., Lawlor, D., Lynch J., & Smith. G. (2006). Indicators of Socioeconomic Position (Part 1). Epidemiology and Community Health, 60(1), 7–12.

20

ACCEPTED MANUSCRIPT Gibbon, M., Labonte, R., & Laverack, G. (2002). Evaluating Community Capacity. Health and Social Care in the Community, 10(6), 485-91. Goodman, R., Speers, M., Mcleroy, K., Fawcett, S., Kegler, M, Parker, E., Smith, S., Sterling, T., & Wallerstein, N. (1998). Identifying and Defining the Dimensions of

RI PT

Community Capacity to Provide a Basis for Measurement. Health Education & Behavior, 25(3), 258-78.

SC

Hawe, P., Noort, M., King, L., & Jordens, C. (1997). Multiplying Health Gains: the critical role of capacity-building within health promotion programs. Health Policy, 39(1), 29-42.

M AN U

Hawe, P., King, L., Noort, M., Gifford, S. & Lloyed, B. (1998). Working invisibly: health workers talk about capacity-building in health promotion. Health Promotion International, 14, 285–295.

Ivory, V., Collings, S., Blakely, T., & Dew, K. (2011). When does Neighbourhood Matter?

TE D

Multilevel relationships between neighbourhood social fragmentation and mental health. Social Science & Medicine, 72, 1993-2002.

Jackson, S., Cleverly, S., Poland, B., Burman, D., Edwards, R., & Robertson, A. (2003).

EP

Working with Toronto Neighbourhoods Toward Developing Indicators of Community

AC C

Capacity. Health Promotion International, 18(4), 339-49. Johnston, R., Propper, C., Sarker, R., Jones, K., Bolster, A., & Burgess, S. (2005). Neighbourhood Social Capital and Neighbourhood Effects. Environment and Planning A, 37(8), 1443.

Jung, M., & Rhee, H. S. (2013). Determinants of Community Capacity Influencing Residents’ Health Status in Seoul, South Korea. Asia-Pacific Journal of Public Health, 25(2), 199-208.

21

ACCEPTED MANUSCRIPT Jung, M., & Viswanath, K. (2013). Does Community Capacity Influence Self-Rated Health? Multi-level contextual effects in Seoul, Korea. Social Science & Medicine, 77, 60-69. Kawachi, I., Kim, D., Coutts, A., & Subramanian, S. V. (2004). Commentary: Reconciling

RI PT

Three Accounts of Social Capital. International Journal of Epidemiology, 33, 682-90. Kearns, R. A., Lewis, N., McCreanor, T., & Witten, K. (2009). ‘The status quo is not an

option’: Community impacts of school closure in South Taranaki, New Zealand. Journal of

SC

Rural Studies, 25(1), 131-40.

Labonte, R. (1994). Health Promotion and Empowerment: Reflections on Professional

M AN U

Practice, Health Education & Behavior, 21(2), 253-68.

Labonte, R., & Laverack, G. (2001). Capacity Building in Health Promotion, Part 1: for whom and for what purpose. Critical Public Health, 11(2), 111-27. Laverack, G., (2005). Evaluating Community Capacity: Visual representation and

TE D

interpretation. Community Development Journal, 41(3), 266-76.

Lempa, M., Goodman, R., Rice, J., & Becker, A. (2006). Development of Scales Measuring

298-315.

EP

the Capacity of Community-Based Initiatives. Environmental & Occupational Health, 35(3),

AC C

Liberato, S., Brimblecombe, J., Ritchie, J., Ferguson, M., & Coveney, J. (2011). Measuring Capacity Building in Communities: A review of the literature. BMC Public Health, 11(850), (10pp.), http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3229539/pdf/1471-2458-11-850.pdf Lovell, S. A. (2009). Social Capital: The panacea for community? Geography Compass. 3(2), 781-96.

22

ACCEPTED MANUSCRIPT Lovell, S. A., Kearns, R. A., & Rosenberg, M. (2011). Community capacity building in practice: Constructing its meaning and relevance to health promoters. Health and Social Care in the Community. 19(5), 531-4.

Natural Resources an International Journal, 23(5), 401-16.

RI PT

Magis, K. (2010). Community Resilience: An indicator of social sustainability. Society &

Mansuri, G., & Rao, V. (2004). Community-Based and -Driven Development: A critical

SC

review. The World Bank Research Observer, 19(1), 1-39.

McIntyre, S., Ellaway A., & Cummings, S. (2002). Place effects on health: how can we

M AN U

conceptualise, operationalise and measure them? Social Science & Medicine, 55(1), 125-39. Maclellan-Wright, M., Anderson, D., Barber, S., Smith, N., Cantin, B., Felix, R., & Raine, K. (2007). The Development of Measures of Community Capacity for Community-Based Funding Programs in Canada. Health Promotion International, 22(4), 299-306.

TE D

Peterson, N. A., Speer, P. W., & McMillan, D. W. (2008). Validation of a Brief Sense of Community Scale: Confirmation of the Principal Theory of Sense of Community. Journal of

EP

Community Psychology, 36(1), 61-73.

Poortinga, W. (2012). Community Resilience and Health: The role of bonding, bridging, and

AC C

linking aspects of social capital. Health & Place, 18, 286-95. Putnam, R. (2000). Bowling Alone: The collapse and revival of American Community. Simon & Schuster.

Robertson, A., & Minkler, M. (1994), New Health Promotion Movement: A critical examination. Health Education Quarterly, 21 (3), 295-312. Roussos, S. T., & Fawcett, S. B. (2000). A Review of Collaborative Partnerships as a Strategy for Improving Community Health. Annual Review of Public Health, 21, 369-402.

23

ACCEPTED MANUSCRIPT Sampson, R., Raudenbush, S., & Earls, F. (1997). Neighborhoods and Violent Crime: A Multilevel Study of Collective Efficacy. Science, 2777(5328), 918-24. Smith, B. Tang. K. & Nutbeam, D. (2006). WHO Health Promotion Glossary: New terms. Health Promotion International, 21(4), 340-45.

RI PT

StataCorp. 2013. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP. Statistics New Zealand. (2013). Dataset: Age by Sex, for the Census Usually Resident

Population Count, 2013. Retrieved from http://nzdotstat.stats.govt.nz/wbos/index.aspx

SC

Statistics New Zealand. (2013). Dataset: Ethnic group (grouped total responses), for the

M AN U

Census Usually Resident Population Count, 2013. Retrieved from http://nzdotstat.stats.govt.nz/wbos/index.aspx

Statistics New Zealand. (2013). Dataset: Highest Qualification, Age Group and Sex, for the Census Usually Resident Population Count Aged 15 Years and Over, 2001. Retrieved from

TE D

http://nzdotstat.stats.govt.nz/wbos/index.aspx

Subramanian, S., Lochner, K., & Kawachi, I. (2003). Neighbourhood Differences in Social Capital: A compositional artefact or a contextual construct? Health & Place, 9, 33-44.

EP

Szreter, S., & Woolcock, M. (2004). Health by Association? Social Capital, Social Theory

AC C

and the Political Economy of Public Health. International Journal of Epidemiology, 33(4), 650-67.

Veenstra, G. (2001). Social Capital and Health. ISUMA Canadian Journal of Policy Research, 2 (1), 72-81.

Veenstra, G. (2002). Social Capital and Health (plus wealth, income inequality and regional health governance). Social Science & Medicine, 54(6), 849-68.

24

ACCEPTED MANUSCRIPT Woelk, G., (1982). Cultural and Structural Influences in the Creation of and Participation in Community Health Programmes. Social Science & Medicine, 35(2), 419-24. Yurdugül, H., (2008). Minimum sample size for Cronbach’s coefficient alpha: A monte-

AC C

EP

TE D

M AN U

SC

RI PT

carlo study. H. U. Journal of Education, 35:397–405.

25

ACCEPTED MANUSCRIPT Appendix A: 26-Item Community Capacity Instrument

a.

I support the local school whenever I can

b.

I attend local events whenever I can

c.

I rarely give my money or time to local groups*

d.

Participating in local clubs and events is good for the community

Leadership a.

The most important issues affecting [place name] are being addressed If I share my ideas and opinions with local leaders they will listen

c.

My town/neighbourhood has strong leaders who are moving it forward

d.

[Place name]’s community leaders don’t work together (C11)*

Social Cohesion Most people in the community can be trusted

b.

I don’t feel welcome to join local groups and activities*

M AN U

a. c.

Residents are friendly and inclusive of newcomers

d.

[Place name] is a close-knit community

e.

I have little in common with most people who live here*

Sense of Place

SC

b.

RI PT

Participation

a. I have a good understanding of [place name]’s history

TE D

b. I see how economic changes have affected [place name] c. I am proud to be a resident of [place name] Community attitudes

a. [Place name] has a positive future

b. What is good for the neighbourhood is good for me f.

EP

e. [Place name] residents have many skills and talents [Place name]’s youth often go on to achieve great things

AC C

Problem Assessment

a. I frequently discuss community issues with my friends and neighbours b. I have a good understanding of the strengths and needs of [place name] c.

I am quick to work with others when I see a need within the community

d. [Place name] has had more success than failure in resolving local issues e. [Place name]’s residents bounce back in hard times f.

If there were a serious problem in this community the people here could get together and solve it

* Item is reverse scored

ACCEPTED MANUSCRIPT

Leadership

Leadership is strong and participatory; leaders are accessible

Connections

Residents are trusting and inclusive of others

Sense of Place

Residents are familiar with their town's history and have an affinity with the place

Community attitudes

Residents have a positive attitude toward their community and its future

Problem Assessment

Residents communicate to identify problems and take action

Table 2: Demographics

Sample characteristics of responders Milton Winton Riverto n East 145 83 42 36 68 (48) 35 (44) 16 (38) 16 (44)

Overall

Mataura

Milton

306 135 (45)

51

48

48

Female

75 (52)

20 (56)

165 (55)

49

52

Missing 18–30 31–40 41–50 51–60 61-70 71+ Missing European Māori Other Missing <1 year 1–5 years 6–10 years

2 13 (9) 26 (18) 21 (15) 27 (19) 31 (22) 24 (17) 3 106 (76) 28 (20) 6 (4) 5 4 (3) 28 (20) 13 (9)

0 6 (17) 9 (25) 4 (11) 6 (17) 7 (19) 4 (11) 0 30 (86) 3 (9) 2 (6) 1 4 (11) 8 (22) 6 (17)

6 36 (12) 46 (15) 44 (15) 61 (20) 60 (20) 52 (17) 7 243 (83) 38 (13) 12 (4) 13 14 (5) 57 (19) 27 (9)

19 15 18 19 17 12

28

Ethnicity (prioritised)

Years lived in location

26 (62)

EP

44 (56)

4 10 (13) 7 (9) 15 (19) 20 (25) 13 (16) 14 (18) 4 70 (91) 5 (6) 2 (3) 6 3 (4) 13 (16) 6 (8)

AC C

Age

Male

TE D

Mataura Total sample Sex

SC

Residents support local groups with their money or time.

M AN U

Participation

RI PT

Table 1: Dimensions of Community Capacity

0 7 (17) 4 (10) 4 (10) 8 (19) 9 (21) 10 (24) 0 37 (90) 2 (5) 2 (5) 1 3 (7) 8 (19) 2 (5)

Census data (%) * Winton Riverton

Overall

National data

46

48

48

52

54

52

52

16 15 17 17 17 17

18 12 15 15 14 25

11 13 14 19 21 22

16 14 16 17 17 20

22 17 17 17 13 12

17

8

18

17

14

Income

Religion

0 (0) 6 (17) 12 (33) 0 9 (25) 23 (64) 4 (11) 0 2 (6)

18 (6) 24 (8) 160 (53) 6 50 (17) 188 (64) 58 (20) 10 21 (7)

Secondary Technical University Missing Full-time (including seasonal) Part-time (including seasonal) Retired Student Unemployed Sick leave Household Other Missing –20k –30k –50k –70k 70k+ Missing None Christian Other Missing

101 (72) 24 (17) 5 (4) 5 64 (45) 23 (16) 31 (22) 0 (0) 4 (3) 3 (2) 11 (8) 5 (4) 4 19 (15) 26 (20) 25 (20) 34 (27) 23 (18) 18 47 (36) 83 (63) 2 (2) 13

57 (74) 11 (14) 5 (6) 6 35 (45) 12 (15) 20 (26) 1 (1) 1 (1) 4 (5) 5 (6) 0 (0) 5 14 (19) 8 (11) 21 (29) 16 (22) 14 (19) 10 17 (25) 51 (74) 1 (1) 14

25 (60) 8 (19) 4 (10) 0 20 (49) 3 (7) 10 (24) 1 (2) 2 (5) 4 (10) 1 (2) 0 (0) 1 5 (14) 1 (3) 17 (47) 3 (8) 10 (28) 6 10 (24) 31 (74) 1 (2) 0

19 (53) 11 (31) 4 (11) 0 14 (39) 8 (22) 7 (19) 0 (0) 0 (0) 3 (8) 4 (11) 0 (0) 0 6 (18) 7 (21) 8 (24) 9 (26) 4 (12) 2 17 (49) 18 (51) 0 (0) 1

202 (68) 54 (18) 18 (6) 11 133 (45) 46 (16) 68 (23) 2 (1) 7 (2) 14 (5) 21 (7) 5 (2) 10 44 (16) 42 (16) 71 (26) 62 (23) 51 (19) 36 91 (33) 183 (66) 4 (1) 28

AC C

Showing n(%) in each case

* All Census data is from 2013 except education which is from 2001 † Ethnicity data from the Census is for ages 20+

SC

3 (7) 4 (10) 22 (52) 0 7 (17) 24 (59) 10 (24) 1 5 (12)

M AN U

Employment

6 (8) 5 (6) 46 (58) 4 11 (14) 50 (65) 16 (21) 6 4 (5)

TE D

Education †

9 (6) 9 (6) 80 (56) 2 23 (16) 91 (64) 28 (20) 3 10 (7)

EP

Marital status

11–15 years 16–20 years 21+ years Missing Single Married/de facto Separated/divorced/widow Missing Primary

RI PT

ACCEPTED MANUSCRIPT

13 2

16 3

18 5

14 5

15 4

19 11

ACCEPTED MANUSCRIPT Table 3: Items and Cronbach’s alpha for the scale and subscales

Connections subscale

5

Sense of place subscale

3

Community attitudes subscale

4

Problem assessment subscale

6

0.87 0.86 0.49

0.89 0.89 0.61

0.91 0.90 0.82

0.91 0.91 0.76

0.89 0.88 0.62

0.70

0.83

0.84

0.77

0.59

0.66

RI PT

4

Overall

SC

Leadership subscale

I support the local school whenever I can, I attend local events whenever I can, Participating in local clubs and events is good for the community, I rarely give my money or time to local groups (R) If I share my ideas and opinions with local leaders they will listen, My town has strong leaders who are moving it forward, [town]'s community leaders don't work together (R), The most important issues affecting [town] are being addressed I don't feel welcome to join local groups and activities (R), Mataura is a close-knit community, Residents are friendly and inclusive of newcomers, Most people in the community can be trusted, I have little in common with most people who live here (R) I have a good understanding of Mataura's history, I see how economic changes have affected Mataura, I am proud to be a resident of Mataura Mataura has a positive future, What is good for the neighbourhood is good for me, Mataura residents have many skills and talents, Mataura's youth often go on to achieve great things I frequently discuss community issues with my friends and neighbours, I am quick to work with

Cronbach’s alpha coefficients Milton Winton Riverton

0.69

M AN U

41 26 4

Mataura

0.62

0.73

0.63

0.77

0.54

0.67

0.66

0.71

0.70

0.51

0.72

0.71

0.63

0.66

0.76

0.76

0.67

TE D

All items Shortened scale Participation subscale

Included items

EP

Number of items

0.61

AC C

Scale/subscale

ACCEPTED MANUSCRIPT

AC C

EP

TE D

M AN U

SC

RI PT

others when I see a need in the community, I have a good understanding of the strengths and needs of Mataura, If there were a serious problem in this community the people here could get, Mataura has had more success than failure in resolving local issues, Mataura's residents bounce back in hard times (R) Denotes reverse scored item. Alphas ≥ 0.70 are shown in bold.

ACCEPTED MANUSCRIPT Table 4: Correlations between scale and subscales Attitudes

Problem

0.41 0.52 0.24

0.51 0.28

0.41

SC

RI PT

Leadership

AC C

EP

TE D

M AN U

Connections Place Total score excluding particular subscale Connections 0.78 0.64 Place 0.63 0.51 0.31 Leadership 0.73 0.58 0.55 0.32 Attitudes 0.73 0.60 0.52 0.42 Problem 0.82 0.70 0.54 0.50 Participation 0.58 0.42 0.33 0.33 Correlations are Pearson’s Product Moment correlations. All p<0.001. Total score including all subscales

ACCEPTED MANUSCRIPT

Table 5 showing the regression results wasn’t here. This is the version I emailed on 30-07-2014 Table 5: Predictors of total score

Years lived in location

Marital status

Education

Employment

Income

1–5 years 6–15 years 16–20 years 21+ years (ref single) Married/de facto Separated/divorced/widow (ref primary) Secondary Technical University (ref full-time, including seasonal) Part-time (including seasonal) Retired Student/ unemployed/household Sick leave (ref –20k) –30k –50k –70k

6.9 (-1.1, 15.0) 9.0 (1.0, 17.1) 11.7 (4.9, 18.5) 17.2 (9.3, 25.1) 285

0.021 -5.2 (-11.7, 1.2) -13.5 (-24.5, -2.6)

294

<0.001 -7.6 (-18.3, 3.1) -8.5 (-19.5, 2.4) -2.3 (-14.3, 9.8) 2.9 (-7.1, 12.9)

288

-10.8 (-23.2, 1.6) -13.2 (-25.8, -0.6) -5.0 (-18.2, 8.2) -5.5 (-17.1, 6.2)

0.133

5.0 (-1.0, 11.0) 7.3 (-0.0, 14.7) 287

RI PT

0.666 <0.001

SC

294 292

0.021 -5.1 (-10.2, -0.0) 5.8 (-0.6, 12.3) 0.1 (-6.8, 7.0) -0.9 (-5.3, 3.4)

TE D

Ethnicity

298

EP

Female sex Age

(ref Mataura) Milton Winton Riverton East (ref male) (ref 18–30) 31–40 41–50 51–70 71+ (ref European) Māori Other (ref <1 year)

283

— — — —

0.384

0.2 (-6.3, 6.7) 4.6 (-1.1, 10.4) -1.3 (-8.8, 6.3) -4.3 (-14.8, 6.2)

264

0.552 -3.5 (-10.2, 3.2) -1.6 (-10.0, 6.9)

0.820

-2.1 (-11.0, 6.8) -4.0 (-13.9, 5.9) -0.4 (-12.5, 11.8)

AC C

Location

p-value

Adjusted (n=235) Coefficient p-value (95% CI) <0.001 -11.6 (-17.1, -6.1) 3.4 (-3.5, 10.3) -1.2 (-8.2, 5.7) — — 0.360 5.1 (-3.9, 14.2) 7.4 (-1.7, 16.6) 4.2 (-4.8, 13.3) 8.9 (-2.1, 19.8) 0.126 -5.5 (-12.3, 1.3) -7.9 (-18.9, 3.0) 0.075

M AN U

n

Unadjusted Coefficient (95% CI)

— — — — —

0.127 7.1 (-1.0, 15.1) 9.3 (2.2, 16.4) 6.7 (-0.6, 14.0)

0.160 6.5 (-1.5, 14.5) 10.0 (2.2, 17.9) 8.9 (0.4, 17.4)

ACCEPTED MANUSCRIPT

AC C

EP

TE D

M AN U

SC

RI PT

70k+ 4.2 (-3.4, 11.9) 7.4 (-1.4, 16.1) Christian (ref none) 271 8.0 (3.3, 12.7) <0.001 3.8 (-1.5, 9.1) 0.160 religion Voted in last (ref no/not sure) 293 9.5 (4.5, 14.5) <0.001 9.5 (2.5, 16.5) 0.008 local election Voted in last (ref no/not sure) 293 6.7 (0.9, 12.4) 0.023 -6.0 (-13.3, 1.4) 0.114 national election Volunteered (ref no) 292 11.2 (7.1, 15.3) <0.001 9.5 (4.9, 14.0) <0.001 Note there were 26 items, each scored 1–7, with a potential range of 26–182 for the total score. Variables were included in the adjusted model where they had an unadjusted p<0.20. p-values presented here are Wald tests of categorical variables.

ACCEPTED MANUSCRIPT Research Highlights A scale to measure community capacity was developed and successfully validated

•

Place was a predictor of community capacity beyond that explained by demographics

•

Volunteering correlated with community capacity at individual but not town level

AC C

EP

TE D

M AN U

SC

RI PT

•