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RESEARCH ARTICLE
Cultivating a sense of local community:
Longitudinal population study on social,
psychological, environmental, and technological
factors
Jenna Bergdahl | Rita Latikka | Atte Oksanen
Faculty of Social Sciences, Tampere University, Tampere, Finland
Correspondence
Jenna Bergdahl, Tampere University,
Kalevantie 4, 33100 Tampere, Finland.
Email: jenna.bergdahl@tuni.fi
Funding information
Koneen Säätiö, Grant/Award Number:
202011325
Abstract
Technological environments change social interactions
within local communities, potentially leading to the erosion
of the sense of local community. In this study, we examined
the social, psychological, environmental, and technological
factors that predict a sense of local community. Employing a
longitudinal approach, we analysed predictors of a sense of
local community among Finnish adults aged 18–80 years
(N=1,226) at three time points (spring 2021, spring 2022,
and spring 2023). Our results, based on hybrid multilevel
regression models, showed that greater neighbourhood
engagement and perceived residential environment pleas-
antness positively predicted a sense of local community
over time. Neighbourhood engagement, perceived residen-
tial environment pleasantness, use of neighbourhood tech-
nology, and positive attitude towards neighbourhood
technologies showed positive effects and perceived loneli-
ness and perceived level of urbanization negative between-
person effects, on a sense of local community. The results
shed light on the determinants of a sense of local commu-
nity and carry implications for broader community
Received: 13 December 2023 Revised: 13 April 2024 Accepted: 23 April 2024
DOI: 10.1002/casp.2806
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which
permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no
modifications or adaptations are made.
© 2024 The Authors. Journal of Community & Applied Social Psychology published by John Wiley & Sons Ltd.
J Community Appl Soc Psychol. 2024;34:e2806. wileyonlinelibrary.com/journal/casp 1of15
https://doi.org/10.1002/casp.2806
engagement efforts. Enhancing perceived residential envi-
ronment pleasantness and promoting more active engage-
ment within neighbourhoods could help increase a sense of
local community. Future initiatives may also focus on utiliz-
ing neighbourhood technology as a tool to help strengthen
a sense of local community. Please refer to the Supplemen-
tary Material section to find this article's Community and
Social Impact Statement.
KEYWORDS
community well-being, longitudinal study, neighbourhood
technology, perceived environment pleasantness, sense of local
community
1|INTRODUCTION
The need for belonging is fundamental and universal in human lives (Baumeister, 2012; Baumeister & Leary, 1995;
Deci & Ryan, 2000; Haim-Litevsky, Komemi, & Lipskaya-Velikovsky, 2023; Maslow, 1954). A sense of community
refers to a feeling of belonging, mutual importance among members, and a collective faith in the fulfilment of mem-
bers' needs through their shared commitment to the group (McMillan & Chavis, 1986). A community can be, for
example, a local community, a physical neighbourhood, a virtual space, or a social group. A sense of local community
is defined as to an individual's sense of belonging in, or attachment to, the neighbourhood. A sense of local commu-
nity often involves emotional attachment, identification with community and its values, and participation in commu-
nity activities or helping (Bowe et al., 2022; Kitchen, Williams, & Chowhan, 2012; McMillan & Chavis, 1986; Talò,
Mannarini, & Rochira, 2014).
In recent years, concerns about the erosion of perceived community belonging have intensified, with the corona-
virus disease 2019 (COVID-19) pandemic serving as a catalyst for more urgent discussions on this issue (Jaremka,
Kane, & Bell, 2022; Marzana et al., 2022). As the pandemic imposed physical distancing, it compelled many people to
find new ways of connecting, leading to an increased reliance on virtual connectedness and social media as alterna-
tive sources of belonging (Latikka, Koivula, Oksa, Savela, & Oksanen, 2022; Lee, Malcein, & Kim, 2021; Marzana
et al., 2022). The urgency of addressing these changes in community dynamics has been amplified by the rise of digi-
talization and the growing usage of social media, recognized risk factors for diminishing real-world community ties
(Gatti & Procentese, 2021; Gibbons, 2020; Hampton & Wellman, 2018). Discussions regarding the relationship
between local community ties and technology use have explored various perspectives. These include the potential
interplay between physical and digital neighbourhoods, where digital tools might sustain or enhance local community
experiences (Stevens, Gilliard-Matthews, Dunaev, Woods, & Brawner, 2017). Additional discussions have involved
the potential of technology to facilitate the formation and bolster existing social connections (Gibbons, 2020). In
neighbourhoods where people are geographically close to each other, the structure and fundamental nature of com-
munity is likely to be reshaped and technological interactions somewhat replace face-to-face interactions (Hage,
Wortmann, van Offenbeek, & Boonstra, 2016; Hampton & Wellman, 2018). Considering these shifts, the study of
factors influencing a sense of local community over time has become increasingly relevant.
Cultivating a strong sense of local community is important because it can enhance aspects such as mental health,
life satisfaction, civic engagement, and community development (Kitchen et al., 2012; Procentese & Gatti, 2022;
Rugel, Carpiano, Henderson, & Brauer, 2019; Talò et al., 2014). This cultivation aligns with the fulfilment of the need
for belonging, which in turn benefits psychological and social well-being at individual and collective levels (Allen,
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Kern, Rozek, McInerney, & Slavich, 2021; Haim-Litevsky et al., 2023). Moreover, a sense of local community can
serve as a protective factor, buffering the impacts of social, economic, and technological changes (Bowe et al., 2022;
Li, Sun, He, & Chan, 2011; Procentese, Capone, Caso, Donizzetti, & Gatti, 2020). In previous research, various psy-
chological, social, and environmental factors have been found to support a sense of belonging (Allen et al., 2021) and
sense of community (Long & Perkins, 2007) in cross-sectional settings. Specifically, community engagement
and active participation in community activities are connected to a stronger sense of community (Albanesi,
Cicognani, & Zani, 2007; Bowe et al., 2022; Mannarini & Fedi, 2009; Talò et al., 2014; Tang, Chi, & Dong, 2017). Per-
ceptions of environmental safety and pleasantness are also linked with stronger community belonging and better
well-being (Bond et al., 2012; Latikka et al., 2023; Rugel et al., 2019). Physical environmental design has the potential
to encourage social interaction and strengthen the sense of community, for example, by focusing on accessibility and
usability of spaces (Brown et al., 2009; Wood, Giles-Corti, & Bulsara, 2012). In turn, loneliness has been found to
have a negative association with the sense of a local community (Latikka et al., 2023; Prezza, Amici, Roberti, &
Tedeschi, 2001).
Current developments such as social media and virtual communities provide new potential avenues for enhanc-
ing a sense of local community by keeping members connected and engaged (Gatti & Procentese, 2021;
Gibbons, 2020; Latikka et al., 2023). However, it remains somewhat unclear whether social media increases connect-
edness or distances people from their physical communities (Gibbons, 2020; Hampton & Wellman, 2018). A growing
body of literature supports the positive link between using technology (e.g., social media and mobile technology) and
local community belonging (Gatti & Procentese, 2021; Gibbons, 2020; Han, Shih, Beth Rosson, & Carroll, 2016;
Latikka et al., 2023). Less is known about the link between attitudes towards using neighbourhood technology and a
sense of local community. The integration of technological factors into the analysis of community belonging is
a novel aspect of this study. Moreover, the research literature on predictors of a sense of community and belonging
has been dominated by cross-sectional studies, with longitudinal studies in this area being scarce (Allen et al., 2021;
Gibbons, 2020; Procentese et al., 2020).
In this longitudinal study, we examined social, environmental, psychological, and technological factors predicting
a sense of local community. Our study is grounded on theoretical perspectives of the need-to-belong theory
(Baumeister, 2012; Baumeister & Leary, 1995) and sense of community theory (McMillan & Chavis, 1986). Further-
more, we rely on empirical evidence on the connections of a sense of local community with use of technology
(Gatti & Procentese, 2021; Gibbons, 2020; Han et al., 2016; Latikka et al., 2023) and perceived environmental factors
(Bond et al., 2012; Brown et al., 2009; Latikka et al., 2023; Rugel et al., 2019; Wood et al., 2012). The findings shed
light on the longitudinal determinants of a sense of community belonging, which may be useful for community
engagement efforts.
2|NEED-TO-BELONG AND SENSE OF COMMUNITY PERSPECTIVES
We applied a theoretical framework that combines theoretical approaches on the need-to-belong
(Baumeister, 2012; Baumeister & Leary, 1995) and sense of community (McMillan & Chavis, 1986). According to the
need-to-belong theory, humans have an intrinsic motivation to form and maintain meaningful interpersonal relation-
ships. This need for belongingness is considered a fundamental and universal aspect of human life, with deep evolu-
tionary roots. Fulfilling this need is associated with several mental and physical health benefits, including reduced
stress, better immune function, and higher self-esteem. In contrast, failing to meet this need can lead to negative
psychological effects such as loneliness, depression, and anxiety (Allen et al., 2021; Baumeister & Leary, 1995). The
sense of community theory predicts that the essence of community lies in members' feelings of belonging, the impor-
tance of each member to the group and to one another, and a collective conviction that the community will address
each member's needs through their commitment to be together. The psychological and social aspects of community
belonging are captured through four core elements (fulfilment of needs, influence, integration, and membership) as
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well as shared emotional connection (McMillan & Chavis, 1986). These core elements of a sense of community could
be fostered through a variety of social, environmental, and technological factors, thereby helping to satisfy the
human need to belong.
3|EMPIRICAL EVIDENCE ON SENSE OF COMMUNITY
Loneliness is a psychological and social factor that is closely linked with a sense of belonging (Lim, Allen, Furlong,
Craig, & Smith, 2021). Loneliness is often defined as a perceived discrepancy between social relationships one has
and would like to have, in terms of their quality or quantity (Peplau & Perlman, 1982). Loneliness and a sense of local
community belonging have been found to be negatively associated (Latikka et al., 2023; Prezza et al., 2001),
highlighting how feelings of isolation are linked with one's connection to their community. Furthermore, engagement
within neighbourhood communities has been identified as an important predictor of a sense of community belonging
(Albanesi et al., 2007; Bowe et al., 2022; Mannarini & Fedi, 2009; Talò et al., 2014; Tang et al., 2017).
Community engagement typically refers to the active participation of individuals in local activities and decision-
making processes, aimed at enhancing collective well-being and fostering a sense of shared identity and belonging in
a neighbourhood or group. It is associated with various sociodemographic factors such as age, gender, income, edu-
cation, and length of residence (Talò et al., 2014). Previous research has identified various types of community
engagement, including civic, social, and neighbourhood engagement, as well as different participation forms. This
engagement not only involves emotional connection and social cohesion but also encompasses the physical aspects
of community life, such as increased interaction and mobility within a neighbourhood. Greater neighbourhood
engagement is positively connected to a sense of community (Albanesi et al., 2007; Bowe et al., 2022; Mannarini &
Fedi, 2009; Procentese & Gatti, 2022; Talò et al., 2014; Tang et al., 2017). For example, Bowe et al. (2022) found
coordinated local community helping to be associated with increased sense of community and well-being. Addition-
ally, Procentese and Gatti (2022) showed that actively taking on responsibilities and engaging in local relationships
and communal activities are linked with a stronger sense of community.
A sense of local community is also connected to environmental factors. Perceived residential environment pleas-
antness generally refers to the subjective evaluation of one's living area as aesthetically pleasing, safe, and supportive
of well-being. This encompasses the neighbourhood's physical beauty, maintenance, and design, along with level of
urbanization and the presence of green areas and communal areas that encourage social interaction and foster a
sense of community (Bond et al., 2012; Brown et al., 2009; Latikka et al., 2023; Rugel et al., 2019; Wood
et al., 2012). In Brown et al.'s (2009) study, objective built environment and architectural features were linked with
perceived social support and community social processes such as social interactions and behavioural health. Rugel
et al. (2019) supported this view, suggesting that urban planning could facilitate social connections and increase the
sense of community belonging. In Latikka et al.'s (2023) study, greater perceived attractiveness of the environment
was linked to a stronger sense of belonging within a local community.
A sense of local community is also linked with technological factors. In the age of digitalization, technological
factors such as social media and virtual communities can offer alternative ways to connect (Gatti &
Procentese, 2021; Gibbons, 2020; Hampton & Wellman, 2018; Han et al., 2016; Latikka et al., 2023). Gatti and Pro-
centese (2021) found that Instagram offers a new way to experience local communities and spread awareness of
local social opportunities. Similarly, Gibbons (2020) found a positive connection between social media use and
neighbourhood community connection. Based on research by Han et al. (2016), active use of mobile technology is
linked with local community attachment and engagement by enabling social support networks and enhancing individ-
uals' social presence within a community. Latikka et al. (2023) found that the use of neighbourhood information and
communication technology was linked with a stronger sense of belonging to the local community. Neighbourhood
technologies (e.g., social media) may play an important role in community interactions and attachment in the future.
Various forms of information and communication technology could facilitate community building but also pose chal-
lenges and opportunities for fulfilling the need to belong (Gibbons, 2020; Hampton & Wellman, 2018). Research has
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indicated that positive attitudes towards new technologies (e.g., artificial intelligence) are linked to the intention to
use them in the future (Bergdahl et al., 2023; Schepman & Rodway, 2020; Venkatesh, Morris, Davis, & Davis, 2003).
Previous longitudinal studies on predictors of a sense of local community are limited, but some longitudinal evi-
dence can be found. Mesch and Talmud (2010), focused on the influence of involvement in local electronic networks,
determined that community engagement is not primarily driven by internet connectivity, but by the novel platform it
provides for community participation. They also found that internet access and a positive attitude towards technol-
ogy are critical factors in enhancing community belonging. Long and Perkins' (2007) study on five neighbourhoods in
New York City in the mid-1980s showed that social capital elements such as neighbouring, citizen participation,
commitment to collective community improvement, community confidence, community satisfaction, and place
attachment predicted a stronger sense of local community. There is a need for up-to-date longitudinal evidence on
the factors that influence a sense of local community.
4|THIS STUDY
In this longitudinal study, we investigated social, psychological, environmental, and technological factors that
predicted a sense of local community from 2021 to 2023. This information is particularly relevant in a rapidly chang-
ing world where the very fabric of communities is continually being reshaped by technological advancements and
social changes. We grounded our study on theoretical perspectives of the need-to-belong theory (Baumeister, 2012;
Baumeister & Leary, 1995) and sense of community theory (McMillan & Chavis, 1986). According to prior research,
neighbourhood engagement (Albanesi et al., 2007; Bowe et al., 2022; Mannarini & Fedi, 2009; Procentese &
Gatti, 2022; Talò et al., 2014; Tang et al., 2017) and perceived residential environment pleasantness (Bond
et al., 2012; Brown et al., 2009; Latikka et al., 2023; Rugel et al., 2019; Wood et al., 2012) have emerged as predic-
tors of a sense of community in cross-sectional contexts.
The current need is to analyse these factors using a longitudinal design and to examine whether new technologi-
cal elements contribute to a sense of local community. Based on previous literature (Gatti & Procentese, 2021;
Gibbons, 2020; Han et al., 2016; Latikka et al., 2023), we consider that use of neighbourhood technology and a more
positive attitude towards it predict a stronger sense of local community. Understanding the risk and protective fac-
tors of a sense of local community is not only essential in attempts to support individual well-being but also critical
for fostering resilient, cohesive communities in the long run.
We hypothesized the following based on existing research:
•Hypothesis 1. Stronger neighbourhood engagement predicts a stronger sense of local community
over time.
•Hypothesis 2. Stronger perceived residential environment pleasantness predicts a stronger sense
of local community over time.
•Hypothesis 3. Use of neighbourhood technology predicts a stronger sense of local community
over time.
•Hypothesis 4. Positive attitudes towards future neighbourhood technologies predicts a stronger
sense of local community over time.
•Hypothesis 5. Stronger loneliness predicts a lower sense of local community over time.
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5|METHOD
5.1 |Participants and procedure
This study is based on a longitudinal AI in Society Survey study (Principal Investigator: Atte Oksanen). The first time
point (T1) of the survey data was collected in May–June 2021. Participants were Finnish adults aged 18 to 80 years
living in mainland Finland (N=1,226). The follow-up data were collected from the same participants in May–June
2022 (T2; n=828) and May–June 2023 (T3; n=717). The response rate to the T1 survey was 30.81% among all
individuals invited to participate. Among those who completed the first survey, 67.55% also completed the T2 sur-
vey, and 54% completed the T3 survey.
The survey includes participants' perspectives and experiences related to emerging technologies such as AI,
social interactions, well-being, and demographic details. Recruitment of participants took place through an online
panel managed by Norstat Finland. To ensure the panel's quality, Norstat conducts systematic checks and assess-
ments by comparing member profiles against official statistics. When demographic discrepancies are identified,
Norstat implements targeted recruitment strategies to attract individuals from the broader population who have the
requisite characteristics to fill these gaps. We also compared the sample to the Finnish adult population aged 18–
80 years from 2020 using the StatFin service (https://www.stat.fi/tup/statfin/index_en.htm) provided by Statistics
Finland. Our comparison shows that there are no major deviations in age, gender, or area distribution of the partici-
pants (Latikka et al., 2023). The sample's gender distribution closely matched the 18–80-year age group in Finland,
with females comprising 50.08% in the sample and 50.10% per Statistics Finland. Furthermore, regarding age, the
sample aligned with the Finnish 18–80-year age demographic (average age, 48.43 years compared with 48.40 years).
The sample had a marginally higher representation from the Helsinki-Uusimaa region (34.01% vs. 31.24%) and a
slightly lower representation from Northern Finland (10.45% vs. 12.88%) and Eastern Finland (14.84% vs. 15.35%).
The sample featured a marginally higher proportion of individuals with at least a BA degree from a university or uni-
versity of applied sciences compared to the general population (38.25% vs. 36.80%).
An analysis comparing non-respondents between T3 and T1 showed that those who participated in the third
time point were generally older (mean age, 53.10 vs. 48.43 years). In terms of gender distribution, there was no sig-
nificant difference in dropout rates (50.35% vs. 50.08% female). Regional variations were minimal, with participant
proportions in Helsinki-Uusimaa (34.87% vs. 34.01%), Eastern Finland (14.36% vs. 14.84%), and Northern Finland
(10.32% vs. 10.45%).
Participants received information about the objectives of the study and were advised that they could withdraw
from the survey at any stage if they chose to. Furthermore, participants were provided with contact details for the
research project and a link to the privacy statement. Median response times for the surveys were 16.1 (T1), 17.1
(T2), and 16.2 min (T3).
In terms of data cleaning, we conducted quality-check analyses following the research lab's established protocol,
which involved identifying patterns and unusual responses. Responses were only included in the final dataset from
participants who completed the entire survey. Before commencing data collection, ethical approval for the research
protocol was obtained from the Ethics Committee of the Tampere Region (decision 29/2021).
5.2 |Measures
Sense of local community was measured with a 6-item scale (Hawdon, Rasanen, Oksanen, & Vuori, 2014; Räsänen,
Hawdon, Näsi, & Oksanen, 2014) adapted from the sense of community scale (Bachrach & Zautra, 1985). Partici-
pants were asked to indicate the extent to which they agreed with six statements about their local community: “Iam
proud to be a member of my community”;“I trust my neighbors”;“I feel I am part of the community”;“People in my
neighborhood share the same values”;“My neighborhood is a good place to live”; and “People work together to get
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things done for this community.”The response scale ranged from 1 (totally disagree)to7(totally agree). The scale
showed good inter-item reliability based on McDonald's omega coefficients: .89 (T1), .90 (T2), and .90 (T3).
Perceived residential environment pleasantness was measured with a six-item scale. Participants were asked to
what extent they agree with the six statements about their residential environment: “Buildings are at an appropriate
distance from each other”;“Buildings are beautiful”;“The area is comfortable to walk in”;“The area is safe”;“There
are enough outdoor activities for me in the area”; and “There are enough opportunities to meet people in the area.”
The response scale ranged from 1 (totally disagree)to7(totally agree). The scale showed good inter-item reliability
based on McDonald's omega coefficients: .85 (T1), .84 (T2), and .87 (T3).
Neighbourhood engagement was measured with a five-item scale. Participants were asked how often they
“spend time in neighborhood's courtyard/yard”;“walk in the neighborhood”;“move around in the neighborhood
during leisure time”;“have face-to-face conversations with people in the neighborhood”; and “greet people in the
neighborhood.”The response scale ranged from 0 (never)to4(many times a day). The scale showed good inter-item
reliability based on McDonald's omega coefficients: .79 (T1), .80 (T2), and .80 (T3).
Use of neighbourhood technology was measured with a 9-item scale. Participants were asked how often they
use following technologies in their neighbourhood: “neighborhood-focused social media service (e.g., Facebook,
WhatsApp group or channel)”;“neighborhood email list”;“neighborhood website (e.g., housing association resident
page)”;“neighborhood reservation system”;“neighborhood digital display”;“city bike or electric scooter”;“mapping
service and public transportation mobile app”;“location-based mobile game or other application (e.g., geocaching,
Pokémon Go)”; and “robot (e.g., drone).”The response scale ranged from 0 (never)to4(many times a day). The scale
showed good inter-item reliability based on McDonald's omega coefficients: .82 (T1), .80 (T2), and .74 (T3).
Positive attitude towards neighbourhood technologies was measured with a five-item scale. Participants were
asked how favourably they view the increased use of the following technologies to enhance interaction in their
neighbourhood in the future: “neighborhood-targeted social media services”;“neighborhood-targeted digital dis-
plays”;“neighborhood-targeted reservation systems”;“social robots in shared spaces”; and “virtual reality and aug-
mented reality technologies.”The response scale ranged from 1 (totally disagree)to7(totally agree). The scale
showed good inter-item reliability based on McDonald's omega coefficients: .91 (T1), .92 (T2), and .92 (T3).
Loneliness was assessed with three items based on the loneliness scale by Hughes, Waite, Hawkley, and
Cacioppo (2004). Participants were questioned regarding the frequency with which they experience feelings of “a
lack of companionship,”“being left out,”and “isolation from others.”The response scale ranged from 1 (hardly ever)
to 3 (often). The scale showed good inter-item reliability based on McDonald's omega coefficients: .83 (T1), .85 (T2),
and .86 (T3).
Perceived level of urbanization was measured using a single statement: “How urban is your living environment?”
The response scale ranged from 1 (not urban at all)to7(very urban).
Recent move to local community was measured with a question asking the length of residence: “How long have
you lived in your current home?”The response scale ranged from 1 (less than a year)to4(over 10 years). Responses
were coded into a dummy variable indicating those who had moved in during the past year (0 =no, 1 =yes).
Sociodemographic variables. We collected information about age in years, gender (0 =male, 1 =female), level of
education (0 =no university or bachelor's degree, 1 =university or bachelor's degree), monthly gross income on a
scale from 1 (<1,000€)to8(≥7,000€), and working status (0 =not working, 1 =working).
5.3 |Statistical techniques
First, we gathered descriptive statistics and generated a correlation matrix for all study variables. We used a fixed
effects model to test changes at three time points in the dependent variable. Subsequently, the primary analyses
were carried out using linear multilevel hybrid modelling, implemented with the xthybrid command in Stata
(Schunck & Perales, 2017). Hybrid models enable the concurrent examination of within-person effects and between-
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person effects over time. Within-person effects pertain to changes observed over time within individual participants,
whereas between-person effects assess disparities between different participants.
In the hybrid models, a sense of local community, perceived residential environment pleasantness,
neighbourhood engagement, use of neighbourhood technology, positive attitude towards neighbourhood technolo-
gies, perceived level of urbanization, loneliness, work life status, and monthly gross income were time-variant vari-
ables (within- and between-person effects), and the rest were time-invariant variables (between-person effects).
6|RESULTS
Table 1reports a descriptive summary of the variables used in the study. The correlation matrix for all the variables
used in the models is detailed in Appendix A. The average level (mean) of a sense of local community did not change
significantly between the three time points. However, the average change in this variable for individuals across the
timespan was 3.03 indicating changes over time that could be explained by our independent variables. Also, our
independent variables vary over time as shown in Table 1.
Table 2shows the results of the model predicting a sense of local community at three time points. We found sig-
nificant and positive within-person effects of neighbourhood engagement (B=1.46, p< .001) and perceived resi-
dential environment pleasantness (B=2.25, p< .001) on a sense of local community. Regarding between-person
effects, perceived residential environment pleasantness (B=3.73, p< .001), neighbourhood engagement (B=2.11,
p< .001), use of neighbourhood technology (B=0.50, p< .001), and a positive attitude towards neighbourhood
technologies (B=0.52, p=.005) showed positive effects, whereas perceived loneliness (B=0.96, p< .001) and
perceived level of urbanization (B=0.66, p< .001) showed a negative effect on a sense of local community.
Among the control variables, female gender (B=0.31, p=.025), and older age (B=0.36, p=.027) were related to
TABLE 1 Descriptive statistics of the variables (longitudinal sample, N=1,225).
Continuous variables Range
T1 T2 T3 Within-person
differences, SDM SD M SD M SD
Sense of local community 6–42 27.60 7.38 27.68 7.44 27.41 7.45 3.03
Environment pleasantness 6–42 31.58 6.59 31.55 6.40 31.41 6.80 3.09
Positive attitude towards
neighbourhood tech
5–35 18.12 7.50 18.38 7.75 17.43 7.51 3.50
Loneliness 3–9 4.82 1.71 4.69 1.72 4.51 1.67 0.64
Neighbourhood engagement 0–20 9.90 3.72 9.80 3.70 9.75 3.70 1.74
Use of neighbourhood
technology
0–33 5.39 4.38 4.93 4.15 4.57 3.67 1.91
Income 1–8 3.07 1.55 3.24 1.56 3.39 1.61 0.49
Perceived level of urbanization 1–7 4.35 1.90 4.35 1.90 4.31 1.83 0.58
Age 18–80 48.43 17.33 50.30 16.67 51.09 16.15 -
Categorical variables Range n%n%n%
Female 0/1 614 50.12 - - - - -
College/university degree 0/1 469 38.29 - - - - -
Works 0/1 593 48.41 410 49.58 355 49.58 -
Recently moved 0/1 164 13.39 87 10.52 68 9.50 -
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a stronger sense of local community, whereas having a higher education degree (B=0.25, p=.650) and recent
move to local community (B=0.10, p=.293) was associated with a less strong sense of local community.
7|DISCUSSION
In this longitudinal study, we investigated social, psychological, environmental, and technological factors that predict
a sense of local community over time. Our main findings revealed significant and positive within-person and
between-person effects of neighbourhood engagement and perceived residential environment pleasantness on a
sense of local community. In addition, we found positive between-person effects of the use of neighbourhood tech-
nology and positive attitude towards neighbourhood technologies on a sense of local community. Conversely, loneli-
ness and higher perceived level of urbanization had a negative between-person effect on a sense of local
community. Collectively, these findings add knowledge of predictors of a sense of local community.
Our findings provide support for the proposed hypotheses. Supporting H1 and H2, our results showed that
stronger neighbourhood engagement and perceived residential environment pleasantness are significant predictors
of a heightened sense of local community. The results align with previous cross-sectional research (e.g., Bowe
TABLE 2 Hybrid model presenting within-person and between-person effects on sense of local community.
BSE (B)zpvalue
Within-person effects
Environment pleasantness 2.25 0.22 10.20 <.001
Positive attitude towards neighbourhood tech 0.10 .18 0.55 .583
Loneliness 0.23 .22 1.08 .278
Neighbourhood engagement 1.46 .22 6.71 <.001
Use of neighbourhood technology 0.09 .19 0.47 .636
Perceived level of urbanization 0.41 .27 1.52 .128
Income 0.39 .27 1.47 .142
Works 0.13 .26 0.49 .625
Between-person effects
Environment pleasantness 3.73 0.21 17.54 <.001
Positive attitude towards neighbourhood tech 0.52 0.18 2.81 .005
Loneliness 0.96 0.18 5.31 <.001
Neighbourhood engagement 2.11 0.17 12.57 <.001
Use of neighbourhood technology 0.50 0.13 3.62 <.001
Perceived level of urbanization 0.66 0.15 4.27 <.001
Income 0.00 0.20 0.02 .986
Works 0.10 0.18 0.57 .569
Controls
Female 0.31 0.14 2.24 .025
Age 0.36 0.16 2.21 .027
Recently moved 0.10 0.10 1.05 .293
College/university degree 0.25 0.14 1.84 .650
Note: All independent variables have been standardized in the model. The model includes 2,768 observations derived from
1,225 participants.
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et al., 2022; Brown et al., 2009; Latikka et al., 2023; Procentese & Gatti, 2022) and underscore the importance of
active participation in community life and the quality of the living environment in fostering a sense of local commu-
nity. Consistent with H3 and H4, the use of neighbourhood technology and positive attitudes towards future
neighbourhood technologies emerged as significant between-person level predictors, suggesting that digital tools
can play pivotal roles in supporting community connectedness in an increasingly digitized world (e.g., Gatti &
Procentese, 2021; Gibbons, 2020; Latikka et al., 2023). Contrasting these positive effects, our results also confirm
the negative relationship between loneliness (H5) and a sense of local community, echoing the findings from previ-
ous cross-sectional studies (e.g., Latikka et al., 2023). This highlights the critical role of addressing loneliness as a fac-
tor that is related to a lower sense of local community.
Altogether, our study adds knowledge to existing research by providing longitudinal evidence of predictors of a
sense of local community. The longitudinal approach allows us to observe not just static snapshots, but the evolving
nature of these relationships over time. In doing so, we contribute to filling the gap identified in the literature con-
cerning the need for longitudinal studies in this area (e.g., Allen et al., 2021; Gibbons, 2020; Procentese et al., 2020).
The integration of technological factors into the analysis of a sense of local community is also a novel aspect of this
study. Use of neighbourhood technology and the positive attitude towards neighbourhood technologies emerged as
significant between-person predictors, highlighting the potential benefits of technological advancements in
supporting local communities (Gatti & Procentese, 2021; Gibbons, 2020). This aligns with the increasing digitization
of social interactions and suggests that future community-development initiatives could benefit from incorporating
technological platforms to foster community engagement.
We also identified a negative correlation between a higher perceived level of urbanization and a sense of local
community, which may result from individual experiences with the environment or from limited opportunities for
engagement within it (Rugel et al., 2019; Talò et al., 2014). Previous research has acknowledged that social media
activities related to the community can enhance social meaning and livability in urban areas and strengthen individ-
uals' connections to their community (Gatti & Procentese, 2021; Gibbons, 2020). Neighbourhood technologies might
provide new opportunities for various types of neighbourhood engagement efforts and assist in fostering a sense of
local community in the future.
7.1 |Theoretical and practical implications
The implications of this study are multifaceted, encompassing both theoretical and practical insights. Theoretically,
our research extends existing community and social psychology frameworks by exploring how social, psychological,
environmental, and technological factors (within and between individuals) influence a sense of local community.
Grounded in the need-to-belong theory (Baumeister, 2012; Baumeister & Leary, 1995) and the sense of community
theory (McMillan & Chavis, 1986), our findings reinforce the idea that neighbourhood engagement and a pleasant
residential environment are strong predictors of a sense of local community. This enhances our understanding of
how communal spaces and active participation contribute to a sense of community in a local context. In addition, we
shed light on the evolving role of technology in community dynamics, as our results indicate that the use of
neighbourhood technology and positive attitudes towards future neighbourhood technologies are positively related
to a sense of local community. This advancement can prompt further theoretical investigation into how ongoing digi-
tal innovations are transforming traditional notions of a sense of local community.
From a practical perspective, our findings have implications for urban planning and community development.
Urban planners and community developers are encouraged to incorporate residents' psychological and social needs
into neighbourhood designs, creating environments that are aesthetically pleasing, accessible, and interactive to fos-
ter stronger community ties. Specific interventions might include the development of community centres that lever-
age both traditional and digital platforms to cater to the diverse needs of community members, enhancing both
physical and digital engagement.
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Community organizers and policymakers should also promote active engagement through traditional and digital
platforms to cater to community members' diverse needs of community members. This aligns with the increasing dig-
itization of social interactions and suggests an evolving role of technology in enhancing community dynamics. More-
over, our research suggests that there is a negative correlation between loneliness and a sense of local community,
emphasizing the need for interventions that address such experiences to strengthen community ties. Potential inter-
ventions could include using ICT technology to detect loneliness and more effectively target programmes that con-
nect isolated individuals with local community resources and social events.
7.2 |Limitations and future directions
Although this study offers valuable insights, it is not without limitations. Although our model is comprehensive,
including social, psychological, environmental, and technological factors, it may not fully capture the entire range of
elements influencing a sense of local community. In this study, we focused on physical neighbourhoods as local com-
munities and the sense of local community within them. One can still conceptualize one's own local community in
other ways, such as through a virtual community, a social group, or a larger part of the town. In addition, the study's
focus on Finnish adults may limit the generalizability of the findings. With the sample limited to the Finnish popula-
tion, where the age structure is skewed towards older individuals, the sample's average age is also relatively high,
reflecting the age structure of the Finnish population. This may affect the generalizability of the findings to younger
demographics or populations with a different age distribution. Conducting comparative studies across different cul-
tural contexts would enhance our understanding of universal and culture-specific factors that contribute to a sense
of local community.
Our study's longitudinal design provides ground for future research on causal relationships and long-term trajec-
tories in local communities. Such research can help identify targeted interventions that nurture a resilient sense of
local community amidst ongoing societal and technological changes. Future research can build upon the current find-
ings to develop more targeted and effective community-building strategies.
Our study did not directly measure the level of competence in using neighbourhood ICT. Future studies could
include general ICT skills in the models investigating sense of local community. Future research could also investigate
more nuanced how neighbourhood ICT is adopted and used in different communities, as well as what meanings peo-
ple give to technology-enabled interactions in the neighbourhood context.
8|CONCLUSION
Our study highlights the social, psychological, environmental, and technological predictors of a sense of local commu-
nity. It affirms the importance of neighbourhood engagement, perceived environmental pleasantness, and technolog-
ical integration in positively influencing a sense of local community. The insights gleaned are not only academically
significant but also have practical implications for community development and planning. They underscore the neces-
sity for inclusive and technology-integrated strategies to build strong, resilient communities. As we navigate the chal-
lenges of a rapidly changing world, understanding and nurturing these facets of a sense of local community become
increasingly vital for the well-being of individuals and the cohesion of societies at large. In an era in which communi-
ties are continually evolving within a digital and interconnected landscape, our findings offer a timely, important con-
tribution to our understanding of the elements that connect individuals to their local communities.
AUTHOR CONTRIBUTIONS
Jenna Bergdahl: Conceptualization, data curation, formal analysis, investigation, methodology, visualization, writing—
original draft, writing—review and editing. Rita Latikka: Conceptualization, data curation, funding acquisition,
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investigation, writing—original draft, writing—review and editing. Atte Oksanen: Conceptualization, data curation,
funding acquisition, investigation, methodology, project administration, resources, supervision, validation, writing—
original draft, writing—review and editing.
FUNDING INFORMATION
This research received funding from the Kone Foundation (Urban utopias and dystopias: artificial intelligence in art
and society [UrbanAI] project 2021–2024, Grant 202011325, PI: Atte Oksanen).
CONFLICT OF INTEREST STATEMENT
The authors declare no potential conflict of interests.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study will be made available in the Finnish Social Science Data Archive
after the UrbanAI project.
ETHICS STATEMENT
The ethics committee of the Tampere region in Finland declared in a 2021 statement that the protocol for this
research did not present any ethical issues (Statement 29/2021).
ORCID
Jenna Bergdahl https://orcid.org/0009-0006-7217-4159
Rita Latikka https://orcid.org/0000-0003-3798-0017
Atte Oksanen https://orcid.org/0000-0003-4143-5580
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SUPPORTING INFORMATION
Additional supporting information can be found online in the Supporting Information section at the end of this
article.
How to cite this article: Bergdahl, J., Latikka, R., & Oksanen, A. (2024). Cultivating a sense of local
community: Longitudinal population study on social, psychological, environmental, and technological factors.
Journal of Community & Applied Social Psychology,34(3), e2806. https://doi.org/10.1002/casp.2806
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12345678910111213
Sense of local community 1.00
Environment pleasantness 0.61*** 1.00
Positive attitude towards
neighbourhood tech
0.11** 0.13*** 1.00
Loneliness 0.35*** 0.29*** 0.08** 1.00
Neighbourhood engagement 0.46*** 0.28*** 0.17*** 0.17*** 1.00
Use of neighbourhood
technology
0.11** 0.03 0.30*** 0.05 0.28*** 1.00
Female 0.06* 0.03 0.03 0.04 0.07* 0.03 1.00
College/university degree 0.01 0.05 0.14*** 0.02 0.08* 0.03 0.03 1.00
Income 0.10** 0.11** 0.04 0.18*** 0.13*** 0.07* 0.20*** 0.32*** 1.00
Works 0.05 0.04 0.10** 0.04 0.03 0.06* 0.05 0.12*** 0.39*** 1.00
Perceived level of urbanization 0.12*** 0.12*** 0.15*** 0.06* 0.06* 0.08** 0.02 0.15*** 0.04 0.02 1.00
Recently moved 0.11*** 0.09** 0.09** 0.08* 0.00 0.08* 0.03 0.03 0.08* 0.06 0.10** 1.00
Age 0.15*** 0.14*** 0.23*** 0.30*** 0.00 0.18*** 0.03 0.03 0.16*** 0.34*** 0.05 0.52 1.00
Note: ***p< .001, **p< .01, *p< .05.
APPEN DI X A : Zero-order correlations of the study variables at T1
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