# Saharaline: A Collective Social Support Intervention for Teachers in Low-
Income Indian Schools

Rama Adithya Varanasi  Department of Information Science, Cornell
UniversityIthacaNYCUSA ,  Nicola Dell  Department of Information Science, the
Jacobs Institute, Cornell TechNew YorkNYUSA and  Aditya Vashistha  Department
of Information Science, Cornell UniversityNew YorkNYUSA

(2024)

###### Abstract.

This paper presents Saharaline, an intervention designed to provide collective
social support for teachers in low-income schools. Implemented as a WhatsApp-
based helpline, Saharaline enables teachers to reach out for personalized,
long-term assistance with a wide range of problems and stressors, including
pedagogical, emotional, and technological challenges. Depending on the support
needed, teachers’ requests are routed to appropriate domain experts— staff
employed by educational non-profit organizations who understand teachers’ on-
the-ground realities—who offer localized and contextualized assistance. Via a
three-month exploratory deployment with 28 teachers in India, we show how
Saharaline’s design enabled a collective of diverse education experts to craft
and deliver localized solutions that teachers could incorporate into their
practice. We conclude by reflecting on the efficacy of our intervention in
low-resource work contexts and provide recommendations to enhance collective
social support interventions similar to Saharaline.

social support, collective social support, online support, HCI4D, teachers,
emotional support, problem focused support, informational support, low-income
schools, low-cost intervention, non-profits, education, WhatsApp

††journalyear: 2024††copyright: acmlicensed††conference: Proceedings of the
CHI Conference on Human Factors in Computing Systems; May 11–16, 2024;
Honolulu, HI, USA††booktitle: Proceedings of the CHI Conference on Human
Factors in Computing Systems (CHI ’24), May 11–16, 2024, Honolulu, HI,
USA††doi: 10.1145/3613904.3642617††isbn: 979-8-4007-0330-0/24/05††ccs: Human-
centered computing Empirical studies in HCI††ccs: Human-centered computing
Empirical studies in collaborative and social computing

##  1\. Introduction

Teachers in low-income schools111We use the term ”low-income schools” to
encompass schools that serve low-income communities, including government
schools and affordable private schools that operate with limited resources.,
particularly in the Global South, contend with resource-constrained
environments (Johnson et al., 2005; Mulkeen, 2010). They teach large classes
with immense learning variability among students (Alcott and Rose, 2015; Nath,
2012), prepare teaching materials and pedagogical strategies using scarce
infrastructure (Marishane, 2014; Barrett et al., 2019), and have limited
opportunities for upskilling (Govmda and Josephine, 2005; Ogunniyi and
Rollnick, 2015). Together, these burdens contribute to teachers’ occupational
stress, with increasing evidence pointing to teachers’ lack of job
satisfaction (Basak and Ghosh, 2011), reduced motivation (Bold et al., 2017),
and burnout (Shukla and Trivedi, 2008; Varanasi, 2023).

Increasingly, educational technology organizations and researchers expect
teachers to overcome resource limitations by reconfiguring their personal
smartphones for work, creating additional stressors. For example, research in
low-income private schools in India showed that teachers are expected to use
smartphones to find new ways to prepare, teach, and engage students (India et
al., 2021; Varanasi et al., 2019). At the same time, school management uses
the same smartphones to increase teacher surveillance and stretch teachers’
work responsibilities beyond their work hours (Varanasi et al., 2021b). These
conflicting practices around smartphones have further contributed to new forms
of stress, including technostress (stress induced by technology) and burnout.
Moreover, with the COVID-19 pandemic, technologies that were previously
considered optional have became critical infrastructure for curriculum
preparation and delivery, and other administrative tasks (Ravi et al., 2021a).
The subsequent top-down shifts to hybrid work practices during and after the
pandemic are further exacerbating the already demanding nature of the teaching
profession, impacting teachers’ overall occupational well-being and
productivity (Zhao et al., 2022).

In such challenging circumstances, social support provides a crucial avenue
for teachers to cope with stress and improve their occupational well-being
(Kyriacou, 2001). Social support is a specific coping mechanism where an
individual leverages their social ties and community resources to receive
assistance (Kim et al., 2022). In the context of teaching, social support
plays a vital role in enabling teachers to manage their occupational well-
being, particularly given the constant emotional labor demanded by their jobs
(Kinman et al., 2011). However, providing holistic and personalized social
support in low-income schools poses several challenges. For example,
establishing new social support structures may require school leadership to
re-allocate resources away from other programs and initiatives, or demand
resources and infrastructure (e.g., time, personnel) that schools simply do
not have. Consequently, on-the-ground efforts in low-income schools are often
constrained to general professional development initiatives that lack
personalization (Gavade et al., 2023). As a result, teachers must often rely
on self-developed support structures that add additional pressure to their
already overburdened responsibilities. For example, peer-based social support
initiated by teachers, while effective, tends to increase their peers’
workload (Gavade et al., 2023). Moreover, these structures also skew towards
types of support that are easier to seek (e.g., pedagogical) than those that
are more challenging (e.g., emotional) (Gavade et al., 2023). There is thus a
need for social support structures that provide holistic, personalized
assistance to teachers in ways that do not strain the current ecosystem.

To address this need, we created Saharaline222In Hindi, ‘Sahara’ translates to
‘support.’, a hybrid333We use the term ‘hybrid’ to denote that the
intervention facilitates both online and in-person interaction. sociotechnical
intervention to improve teachers’ occupational well-being in low-income
schools through collective social support. We define collective social support
as a form of support that unites different individuals in the communities
where workers are embedded to provide comprehensive, localized, and
longitudinal assistance. Using this philosophy, Saharaline was deployed on
WhatsApp to bring different educational non-profit organizations (referred to
as support organizations, hereafter) that work in school environments together
to provide social support to teachers (see Figure 1). Teachers across six
different schools in India were informed about the Saharaline service, and
they accessed it by sending messages or calling a WhatsApp number. A
facilitator managing Saharaline’s WhatsApp interface captured their
information. Based on the data, a caseworker working in a support organization
within the community was mapped to the teacher, who recorded the teacher’s key
problems and shared them back with facilitators. Depending on the nature of
the problem, facilitators then assigned a remote expert with relevant
expertise (occupational mental health, technology education, or pedagogical
and content knowledge) to develop solutions to the teacher’s problems.
Subsequently, the facilitator conveyed these solutions to caseworkers who
communicated them to teachers. Saharaline was designed to provide multiple
rounds of such support to teachers, in ways that were manageable within
teachers’ and experts’ current workloads.

We conducted a three-month pilot deployment of Saharaline in India, focusing
on the experiences of 28 teachers and 11 support organization personnel
(facilitators, caseworkers, and experts) as they received and provided various
forms of social support, respectively. Our findings indicate that Saharaline
attracted diverse teachers with many problems, including those with emotion-
focused issues who were otherwise hesitant to seek support through their usual
channels. By building rapport with teachers, caseworkers successfully surfaced
key problems along with their local practices and communicated them to
Saharaline experts. The remote experts collaborated with caseworkers to craft
effective and contextual solutions while carefully navigating the complexities
of teachers’ work practices.

We critically reflect on our findings to discuss Saharaline’s distributed,
versatile approach in delivering collective social support. Our discussion
aims to understand the benefits and challenges it offers to low-resource
working communities, such as teachers. We also unpack the decentralized
knowledge production practices we observed and provide design recommendations
on integrating emerging technologies to increase the efficiency of the
intervention. Finally, we conclude by reflecting on the complexities of
providing social support via WhatsApp, a piece of technology that can itself
be a source of stress for teachers. In sum, our paper makes four
contributions:

  * •

We show how collective social support was effective in surfacing a wide range
of teacher stressors.

  * •

We show how most teachers (n=25) who reached out to Saharaline did so for
multiple rounds of social support, successfully engaging in longitudinal
support during the three month deployment.

  * •

We present different support pathways created by Saharaline stakeholders to
develop scalable social support structures across six schools in three Indian
states.

  * •

We discuss key takeaways to inform future collective social support
interventions and increase their positive impact in low-income working
communities.

##  2\. Background and Related Work

###  2.1. Understanding Dimensions of Social Support

Shumaker and Brownell (1984) define social support as a process of “exchanging
resources” between individuals where either the provider or receiver
explicitly intends to improve the well-being of the receiver. It serves to aid
individuals facing stress and negative well-being (Lazarus and Folkman, 20;
Jolly et al., 2021). While these studies focused on stressors in one’s
personal life, research has shown similar findings for occupational well-being
(Ganster et al., 1986; Liu and Aungsuroch, 2019). In work settings, social
support takes various forms, including peer support (Mercieca and Kelly,
2018), vocational interventions (McGrath et al., 2020), assistive programs
(Kirk and Brown, 2003), mentorship and coaching (Jones et al., 2016).

Regardless of their manifestations, social support structures are typically
governed by three underlying dimensions (Wills, 1991; Taylor, 2011). The first
is the function of support in an individual’s life (House, 1981). Support can
be problem-focused, providing assistance to “manage or alter the problem
causing the stress” (Lazarus and Folkman, 1984). Alternatively, support can be
emotion-focused, intended to help regulate emotional responses to challenges
(Lazarus and Folkman, 1984). Examples include providing emotional warmth and
care (Lazarus and Folkman, 20), network support (Cutrona and Suhr, 1992), and
boosting esteem (Cutrona and Suhr, 1992). The second dimension involves an
individual’s perception and evaluation of their workplace social support
(Sarason et al., 1991). Research has consistently shown a strong positive link
between perceived social support and occupational well-being (Park et al.,
2004; Turner, 1981). The third dimension pertains to the structure of support,
determined by how individuals embed themselves and engage with social networks
(Chronister et al., 2006; Jolly et al., 2021). This support can take two main
forms: individual support, where a person receives one-on-one assistance; a
common example being therapy or mentorship (Vincent-Höper et al., 2020).
Alternatively, the support can be collective, where an individual receives
support as a result of cooperation or collaboration from multiple people
(Archer et al., 2012). What distinguishes collective support from individual
support is the combined effort of several providers to deliver social support
(Bayraktar, 2019). In the following sections, we explore individual and
collective social support around work and technology, especially within
teaching context to make a case for the effectiveness of collective social
support for low-resource teachers to enhance their occupational well-being.

###  2.2. Individual Social Support: Technology, Work & Teaching

The widespread availability of Internet connectivity has opened up avenues for
technology-mediated individual social support, via channels such as emails
(Hutson and Cowie, 2007), forums (Turner et al., 2001), blogs (Rains and
Keating, 2011), and online conversations, including remote therapy (James et
al., 2022). Despite early research showing mixed results (Kraut et al., 1998;
Shaw and Gant, 2002), the proliferation of devices has expanded opportunities
for informational (Coursaris and Liu, 2009), emotional (Buis, 2008), and
network (Ashley et al., 2011) support provided via online personal networks
(Han et al., 2016).

HCI research has also studied individual social support practices within
specific work domains, including upskilling (Dillahunt et al., 2016) and
career transitions (Burke and Kraut, 2013; Garg et al., 2021; Lu and
Dillahunt, 2021). This knowledge has equipped HCI researchers to examine
social support in demanding professions, particularly emotionally taxing work
such as teaching. Teachers have to constantly regulate their emotions while
working in isolation and contending with frequent stress (Madigan and Kim,
2021). The integration of technology into education has further introduced new
forms of technology-enabled stress, putting teachers at the risk of burnout
(Zhao et al., 2022). For example, during COVID-19, transitions to hybrid
teaching exacerbated teachers’ isolation and stress (Penado Abilleira et al.,
2021; Westphal et al., 2022).

In the Global South, where our research is situated, these challenges are
amplified for several reasons. Teachers rely heavily on smartphones for
teaching, given their affordability and adaptability, as opposed to laptops or
desktop computers (Cannanure et al., 2020b). Moreover, these smartphones are
often teachers’ personal devices used for work, introducing complexities not
encountered by educators using primarily school-provided technological
infrastructure (Varanasi et al., 2020). Lastly, the COVID-19 pandemic also
forced teachers, many of whom had limited experience with remote teaching, to
embrace hybrid teaching approaches using smartphones (Ravi et al., 2021b;
Singh et al., 2023). Early studies suggest that this transition has led to
reduced confidence, increased burnout, and higher attrition rates (Varanasi et
al., 2021b). Robust social support systems could be a critical resource for
teachers to combat isolation, enable professional development, and enhance
occupational well-being (Ingersoll and Strong, 2011). Research in this area
has explored the effectiveness of peer interactions among teachers in
facilitating informational, instrumental, and emotional support through online
and offline mediums, resulting in reduced stress levels among educators
(DeWert et al., 2003; Kinman et al., 2011; Paulus and Scherff, 2008).

However, teachers’ access to peer and management-established social support is
contingent on the availability of school resources (Westphal et al., 2022). In
resource-constrained schools, the absence of resources puts the onus on
teachers to establish and maintain their own support networks. For instance,
Gavade et al. (2023) showed how, in low-income Indian schools, teachers’
formal channels for seeking support from school management were virtually non-
existent, forcing teachers to use their own means (e.g., smartphones) to seek
support. Additionally, formal support, requires significant resources from
providers (e.g., management), increasing burdens and hampering functionality
of support programs (Gavade et al., 2023).

###  2.3. Collective Social Support in Work Settings

In contrast to individual social support, collective social support
distributes responsibilities across different roles within the ecosystem,
encouraging multiple individuals to collaborate, coordinate, and deliver
support. Collective social support can manifest as internal, wherein various
roles, such as peers, management, and other stakeholders come together to
assist individuals. This form of support has become common in roles involving
emotional labor, such as hospitality workers (Wu and Chen, 2019), healthcare
workers (Tixier et al., 2009), social workers (Tixier and Lewkowicz, 2016),
gig workers (Uttarapong et al., 2022) and teachers (Varanasi et al., 2020).
With social media communication (e.g., Facebook and WhatsApp) becoming
prominent in workspaces, virtual interactions (e.g., likes, reactions, and
emojis) have increased social connectedness (Varanasi et al., 2018; Carr et
al., 2016) and have provided new pathways for workers to reach multiple people
and seek support. While this form of support reduces the burden on management
by involving different roles within the working community, the overall strain
is still significant for a resource-constrained community (Oreglia and
Srinivasan, 2020).

To overcome this issue, collective social support efforts can also leverage
individuals external to the community (Bayraktar, 2019; Archer et al., 2012).
One strand of research that shapes this notion of collective support is the
collaborative care (sometimes called collective or cooperative care) movement
in healthcare (Archer et al., 2012). Collaborative care mobilizes medical
experts and caregivers across different domains to collaborate and provide
social support tailored to an individual’s needs. Such collaborative care
leverages coordination among multiple specialists, thereby reducing strain not
only on specific medical roles but also on the overall healthcare system. This
type of support has been shown to improve individuals’ well-being when
compared to traditional support (Archer et al., 2012). However, involving
different stakeholders brings about its own challenges. For instance, defining
and maintaining clear boundaries for distinct roles can be challenging
(Vanderlip et al., 2016). Diversifying care also introduces unequal burdens in
maintaining standardized care pathways, posing challenges to effective social
support (Moise et al., 2018).  HCI research has built on these results to
understand how sociotechnical solutions might include non-specialists like
family members in providing collaborative care for vulnerable populations
(Soubutts et al., 2021; Suh et al., 2020). For instance, Hwang et al. (2020)
found that the learnability and ease of use of technological tools are
critical elements for the success of providing and receiving collective
support. In the long run, such instances of successful support translate into
improved coping mechanisms, directly impacting individuals’ abilities to
regulate their stress (Caldeira et al., 2017).

Another strand of research has examined collective social support in resource-
constrained settings (Arueyingho et al., 2023). Similar to collaborative care,
this form of social support engages actors outside the community to provide
support to reduce stress on the system (Ismail et al., 2022). For example, in
Côte d’Ivoire, families and community members volunteered to complement
teachers’ limited resources by providing informal education support for their
children (Madaio et al., 2020). This involved parents, siblings, relatives,
and neighbors sharing the responsibilities of informal teaching. Involving
community members who were invested in the children’s future allowed cost-
effective implementation of support activities (Madaio et al., 2020). However,
a key issue with both these strands of research is their narrow focus on the
individuals or communities where workers (medical specialists, teachers)
provide support (to patients, students), potentially overlooking the well-
being and support needs of the workers themselves (Varanasi et al., 2021b).
These initiatives also focused on specific types of issues (mental health,
learning outcomes) and do not cover other stressors that might be equally
important for occupational well-being (Singh et al., 2023).

Limited research in the Global South, including health (Ismail and Kumar,
2019) and education (Varanasi et al., 2020), has focused on working
communities, particularly the role of intermediaries in providing collective
support to workers. To address the limited resources and substantial
variability in the digital capabilities of these communities, interventions in
this context have adopted an ”asymmetrical” design (Rahman et al., 2021). In
this design, user-facing technologies are developed to be simple and
straightforward, with more complex designs and heavier load on the back-end to
scale the support (Rahman et al., 2021). For example, Cannanure et al. (2020a)
implemented a conversational agent in the backend that teacher trainers could
leverage to consolidate common professional development topics in which
teachers were interested. However, at a high-level such research has
predominantly aimed at addressing specific work-related challenges (e.g.,
productivity through professional development) rather than fostering
comprehensive occupational well-being (Oreglia and Srinivasan, 2020).
Nevertheless, this literature underscores the need for collective social
support practices for low-resource working communities, especially in the
Global South.

Our study expands this literature by designing and deploying Saharaline, a
hybrid collective social support system that is explicitly tailored towards
workers (i.e. teachers) as opposed to the community they serve (i.e.
students). In this novel context, multiple support organizations specializing
in different forms of social support, such as work-related specialization
(pedagogy, content), technology, and mental health, took on distinct roles to
provide social support that was personalized and holistic, focusing beyond
work-related challenges and covering major aspects of occupational well-being.
Through a three-month deployment of Saharaline in low-resource working
communities of teachers, our research explores the feasibility of providing
longitudinal collective social support via a commonly available technology
platform like WhatsApp. In doing so, we sought to answer two research
questions:

RQ1: What are the experiences of support organization personnel in providing
collective social support through a hybrid sociotechnical intervention?
RQ2: How do teachers use a hybrid collective support intervention to improve
their occupational well-being?

##  3\. Methods

Here, we describe our IRB-approved research methods, including Saharaline’s
design, operation, and details of its three-month deployment in low-income
Indian schools (March to May 2022).

###  3.1. The Educational Support Organization Ecosystem in India

Educational support organizations are non-governmental organizations or social
enterprises that collaborate with low-income private and government schools to
enhance educational outcomes through capacity-building initiatives. In India,
where educational non-profit organizations hold the largest proportion among
all non-profit entities (Nit, [n.d.]), such collaborations are common. In
these collaborations, the support organizations can engage at three levels (a)
At the student level, they focus on interacting with students to improve
learning outcomes (Support Organization 3 in our study, Table 2 in the
appendix); (b) At the teacher level, they train teachers through workshops to
enhance their capacities (Support Organization 1 in Table 2); (c) At the
management level, they collaborate with school management to shape school-
level policies and strategies (Support Organization 2 in Table 2).

Regardless of the level at which they operate, support organizations typically
employ two types of personnel. The first works off-site at the organization’s
headquarters, including subject matter experts, leadership, and the management
team, situated outside the school community. These people typically possess
advanced degrees (e.g., education psychology) and contribute their global
awareness and domain-specific knowledge to support organizational efforts. The
second type of personnel works on-site in schools. These people are recruited
from the same local community where the schools are located. They generally
possess a bachelor’s degree and bring a wealth of local knowledge and
experience gained through their work in the community. In this capacity, they
serve as intermediaries between the personnel at the headquarters and the
stakeholders on the ground. Thus, organizations comprise members from both
within and outside the school community, enabling the integration of global
expertise with local context. Support organizations usually visit school
clusters or government offices to advertise their services. If there is
interest, the organization and school sign a Memorandum of Understanding
lasting anywhere between 2 to 5 years.

###  3.2. Design Approach and Objectives

Saharaline was developed collaboratively by three researchers who study
teacher work practices, three support organization members, and four
experienced teachers from low-resource schools. Beyond sharing a common
motivation to positively impact low-income schools, the three support
organizations also shared an overlapping objective of understanding and
addressing challenges teachers face. All organizations had previously
collaborated with the researchers, actively engaging in exploratory projects
that focused on teachers’ sociotechnical practices. Over a four-week period,
all the stakeholders came together to collectively design the overall
architecture of Saharaline using a scenario-based design approach (Carroll,
1997; Schuler and Namioka, 1993) (see Table 3 in the appendix). The first week
involved reviewing literature, including relevant projects in HCI (e.g.,
(Varanasi et al., 2019; Cannanure et al., 2020b)), teacher education (e.g.,
(Govmda and Josephine, 2005; Ogunniyi and Rollnick, 2015)), and decolonial
research (e.g., (Pendse et al., 2022; Smith, 2021)), and sharing stakeholders’
lived experiences on the ground; this utilized a seminar format that resulted
in story scenarios. Example story scenarios included teachers’ experiences of
using smartphones for preparation, teachers’ conversations with parents of
children with learning disabilities, and teachers’ interactions with their
peers in the staff room.

In the second and third week, we conducted co-creation workshops with all the
stakeholders to translate the story scenarios into problem scenarios. For
instance, stakeholders used the finalized stories to derive specific problem
scenarios where smartphone use impacted their preparation process. The problem
scenarios that captured their pain points were then used to finalize the key
design principles. During these workshops, we used affinity diagramming and
expert walkthroughs to capture diverse stakeholder perspectives. The final
week involved translating the finalized design principles into a high-level
design architecture and obtaining feedback on specific implementation pathways
in an attempt to anticipate and address potential challenges that might arise.
All activities were moderated by a researcher and a support organization
personnel. We now briefly discuss the four resultant design objectives for
Saharaline that materialized from this collaboration, followed by the overall
architecture and implementation.

The first design objective was to anchor Saharaline’s support services in
teachers’ lived experiences (Mignolo and Walsh, 2018), allowing Saharaline to
focus on teachers’ challenges localized to their communities. To achieve this
objective, we sought collaboration of support organizations (or educational
NGOs) as social support providers. These organizations work with low-resource
schools to build capacity at various levels (e.g., students, teachers, and
management) through workshops, seminars, and professional development classes.
While none specifically targeted teachers’ overall occupational well-being in
their capacity development efforts, they were aware of the specific
sociotechnical and sociocultural challenges teachers faced in schools.
Recognizing the cascading impact of addressing teachers’ issues on their own
capacity development initiatives, these organizations naturally expressed
interest in engaging with individual teacher problems through Saharaline.
Their awareness of teachers’ local experiences enabled them to better
understand teachers’ stressors, which traditional support systems did not
adequately address.

The second objective was to decentralize Saharaline’s support providers and
deliver collective social support by fostering collaboration among multiple
support organizations (Ogunniyi and Rollnick, 2015). Through this design
objective, we wanted to identify support providers that brought their unique
awareness of school community challenges and complementary expertise in
teacher practices, as well as their pedagogical and content knowledge. Such
diverse perspectives can reduce burden on a single organization by
facilitating the co-creation of efficient support solutions between teachers
and members of support organizations. For example, a low-income school can
have two support organizations working simultaneously, one working to empower
the management to improve the school leadership and administrative capacities,
and the other working with teachers to improve their pedagogical capacities.
These organizations’ functions overlap, leading to cooperation and assistance
that can be leveraged to support teachers. At the same time, these
organizations have different priorities, allowing them to bring their unique
resources and expertise, while reducing their individual efforts.

The third objective was to make Saharaline’s support accessible by offsetting
the power differential (Lazem et al., 2022) that traditionally exists between
the management and teachers, which limits teachers’ support seeking practices
due to potential repercussions. As support organizations occupied a neutral
position outside the conventional hierarchies of the school system, they did
not carry the same complex power dynamics as school management. This allowed
them to gain trust and engage in sensitive conversations, facilitating an in-
depth understanding of teachers’ challenges.

The fourth objective was to ensure that the work involved in using and running
Saharaline would be manageable given stakeholders’ current workloads.
Specifically (i) that teachers could fit it into their overburdened work
schedules and (ii) that the intervention was manageable for support providers
to deliver alongside their organization work. To achieve this, we developed
Saharaline as a hybrid intervention, consisting of both online (i.e.,
WhatsApp-based helpline) and in-person interactions (i.e., meetings with
teachers).

We chose WhatsApp because it is a widespread and familiar tool in low-income
schools due to its ease of use and high adoption rate among teachers in India.
The business version of WhatsApp is geared towards organizations, non-profits,
and businesses, providing automation features (e.g., scheduled greeting
messages, automated replies, predefined shorthand commands) and multi-user
management of a single account. This set-up allowed us to scale the initiative
across multiple schools in different communities. We complemented this
technological choice with in-person support practices that could accommodate
teachers’ busy schedules and provide long-term support.

Figure 1. Saharaline architecture showcasing key stakeholders: (1) teachers in
low-resource schools who contacted Saharaline, (2) facilitators who oversaw
coordination and managed the helpline; (3) caseworkers who interacted with
teacher on behalf of Saharaline; (4) experts who provided the solutions.

Saharaline architecture showcasing key stakeholders, namely teachers in low-
resource schools who contacted Saharaline facilitators who oversaw
coordination and managed the helpline, caseworkers who interacted with teacher
on behalf of Saharaline and experts who provided the solutions.

Figure 2. Breakdown of pathways providing collective social support through
Saharaline; Support represents the conversion of stressor to solutions for
each stage; Actors represent different stakeholders involved in each step;
Data and medium showcase different mediums in which data is produced through
interaction or knowledge production.

Overview of Saharaline pathways being shown in five rows for seven stages of
support. First row depicts support actions in each stage. Second row depicts
actors involved. Third row depicts the data that is created and the fourth row
shows the medium of support.

###  3.3. Saharaline Operation

Figure 1 shows Saharaline’s architecture and stakeholders, while Figure 2
details the steps involved in providing social support to teachers. To avail
support, teachers contacted Saharaline through a WhatsApp message or called
seven days a week between 8am and 8pm. Ensuring daily operation gave teachers
the flexibility to engage with Saharaline at their convenience. Upon
connecting to the helpline (step 1, Figure 2), the teacher received an
automated welcome message with a template for communicating their problem
(i.e., their demographics and overview of their issue) along with a consent
form. Based on the teacher’s reply, two facilitators (first-author and a
support organization personnel, 2 in Figure 1) forwarded the details to the
nearest available caseworker (3 in Figure1) in their community (step 2, Figure
2).

The caseworker then contacted the teacher on behalf of Saharaline and inquired
about the teacher’s well-being (step 3, Figure 2). Caseworkers belonged to the
same community as teachers and worked for support organizations at their
school. They were aware of the teacher’s local context, such as the local
language and their standing in the community, allowing them to capture the
issues comprehensively. Being in the same community also allowed caseworkers
to offer flexible interaction options (online, offline, inside or outside
school) while accommodating teacher’s busy schedules. The caseworker captured
the teacher’s well-being levels, work preferences, standing with school
management and peers, and key problems (stressors) for which the teacher
needed support. These details were recorded in a case file (see supplementary
material for an example) and sent to the facilitators via WhatsApp (step 4,
Figure 2).

The facilitators then routed the case to an appropriate expert (4 in Figure
1). For example, if the teacher’s key stressor was teaching a classroom with
varied learning levels post-pandemic, it was routed to the expert on
pedagogical support (step 5, Figure 2). Other areas of expertise included
occupational mental health, educational content, and educational technologies.
When a case required multiple experts, it was routed to different experts in
parallel. Experts worked remotely from their organization’s headquarters.
Based on the issue and the context provided by the caseworkers, experts
formulated appropriate solutions, resources, and directions for the teacher,
appending them to the case file (step 6, Figure 2). If experts had queries,
they contacted the facilitators, who relayed them to caseworkers for
clarification. The caseworker’s responses were then provided to the experts.
Over time, the case file accumulated all the issues and solutions for the
teacher across multiple interactions.

Once experts added the solutions, facilitators informed the caseworker who
scheduled a follow-up appointment with the teacher to share the solutions
(step 7, Figure 2). A typical support cycle lasted seven days. This timeline
allowed the caseworker to handle multiple cases in parallel while managing
their regular work. To further provide longitudinal social support,
caseworkers reached out to the teacher a few days after providing the solution
to gather feedback and inquire about any additional issues requiring support.
Saharaline repeated the support cycle for several rounds if the teacher had
follow-up questions or shared new problems.

###  3.4. Pilot Deployment

Saharaline was deployed for three months across three states in India (March
to May 2022) in collaboration with four support organizations. Three
organizations that engaged in Saharaline’s design joined the deployment.
Additionally, we advertised the study to other support organizations via a
mailing list. Out of the five organizations that responded, we shortlisted
one. This brought the total number of support organizations to four, which
allowed us to keep the scope of the study manageable. The final list of
support organizations determined the schools in which we advertised
Saharaline. We shortlisted six schools in communities where at least two of
the four organizations had a presence. This incentivized support organizations
to invest in teacher support alongside their regular activities.

After receiving approval from the six schools, support organization personnel
(with the first author) introduced Saharaline to the schools. Support
personnel then advertised Saharaline on a bi-weekly basis in their teacher-
focused WhatsApp groups for the duration of the deployment. Teachers responded
by reaching out to Saharaline (as described in Section 3.3), during which they
were provided with an online consent form that explained the data collection
process in detail. In total, 28 teachers reached out for support during the
deployment.

####  3.4.1. Participants

The six schools comprised 73 teachers. The first two schools were in a remote
community in the state of Meghalaya. Both were government schools, in the same
block, and catered to low-income communities. Out of the two support
organizations working in these schools, one engaged with teachers and one with
the higher management. The second two schools were low-income private schools
in the neighboring semi-urban community of Gujarat. Out of the two support
organizations working in these schools, one focused on students and the other
on the higher management. The last two schools were in two different urban
districts in Karnataka, where support organizations exclusively worked with
teachers. All six schools were fully functional offline (i.e., in person). Out
of the 28 teachers who used Saharaline, 12 taught primary school and 16 taught
secondary school.

We recruited four caseworkers across the six schools, with two caseworkers
each in Karnataka and one each in Meghalaya and Gujarat. The team, which
comprised two women and two men, had the prior experience of working as
support personnel for different organizations for an average of two years
prior to the deployment. They also lived close to the schools where they
provided support. All five caseworkers were college graduates, with an average
age of 26 years.

We recruited five experts from three of the support organizations. They had an
average age of 35 years and an average of 4.5 years of experience in teacher
training, designing educational content, developing educational technologies,
and practicing occupational therapy. Three had master’s degree while one had a
doctoral degree. Three experts identified themselves as women while two as
men. All were located in the cities where the organization’s headquarters were
located (i.e., not in school communities). Table 1 presents the detailed
demographics of all participants.

Teachers (n=28)
---
Gender |  Women: 18 Men: 10
Age (years) |  Min: 25 Max: 54 Avg: 35.6 S.D: 7.6
Education (degree) |  Bachelor’s: 20 Master’s: 8
Region |  Meghalaya: 8 Gujarat: 9 Karnataka: 11
Experience (years) |  Min: 3 Max: 27 Avg: 9.75 S.D: 5.822
Phone use (years) |  Min: 4 Max: 10 Avg: 5.5
Focus Subject |  Languages: 19 Science: 9 Math: 9 Social Studies: 12
School Type |  Government: 16 Private: 12
Saharaline Personnel (n=11)
Gender |  Women: 6 Men: 5
Age (years) |  Min: 25 Max: 42 Avg: 31.8 S.D.: 5.3
Experience (years) |  Min: 3 Max: 15 Avg: 6.4 S.D.: 3.7
Role |  Caseworkers: 4 Experts: 5 Facilitators: 2
Experts’ Specialization |  Education Technologies: 1, Occupational Mental Health: 1, Teacher training: 2 , Educational content creation: 1
Education (degree) |  Master’s: 9 Doctoral: 2
Table 1. Demographic details of teachers and support organization personnel
involved in Saharaline intervention.

####  3.4.2. Data Collection & Analysis

Our deployment produced three types of data that we analyzed to understand
teachers’ and support providers’ experiences. Before collecting data, we
obtained informed consent from all stakeholders. Our first dataset consisted
of case files created for each of the 28 teachers who had contacted the
helpline. The case files contained teachers’ demographics, work preferences, a
log of caseworkers’ observations about teachers’ issues, and any solutions
provided (see supplementary materials for an example case file).

The second dataset consisted of the interactions between teachers,
caseworkers, and experts as part of the support effort. These included
WhatsApp texts and audio messages that captured (1) initial messages that
teachers reached out with when they shared their issues, (2) the caseworkers’
interaction with the teachers through WhatsApp for coordination,
clarification, and solution sharing and (3) interactions between caseworkers
and experts for coordination and follow-up clarifications. In total, we
analyzed 432 messages between the three stakeholder groups.

The third dataset came in the form of interviews that the first author
conducted with the caseworkers (n=11), experts (n=15), and teachers (n=47) to
capture their overall support-providing and seeking experiences during and
after the deployment. High-level topics for teachers included their motivation
for seeking support, their challenges in getting the support, and their
reasons for disengagements with the helpline. Topics for experts and
caseworkers included their custom strategies to engage teachers, their
challenges in working with resource constraints, and their collaboration
strategies.. In total, we obtained 75 hours of interviews and conversational
audio recordings. Lastly, we also analyzed 21 pages of detailed notes captured
by the first author while managing the helpline. Analyzing different forms of
data allowed us to triangulate our findings (Creswell and Miller, 2000) and
establish a strong sense of validity.

We started our analysis by translating the data captured in local languages
(Hindi, and Kannada) into English. Then, we engaged in qualitative coding
using inductive thematic analysis (Terry et al., 2017). We began by taking
multiple passes of all of our data to internalize the different accounts and
perspectives. For artifacts and messages, we began by going through the
message logs, similar to (Varanasi et al., 2021a), to conduct multiple rounds
of open coding. Our unit of analysis was a single message sent by an
individual participant. Even if the participant broke the message into
multiple lines, we treated it as a single message. All the researchers avoided
any preconceived notions while constructing the codes and subsequent
categories. We followed a similar approach for the interview data. A second
layer of internal validity was achieved via peer debriefing (Creswell and
Miller, 2000) with multiple researchers, both external and internal to the
study. Our analysis resulted in 77 codes (e.g., “sources of tension”,
“material assistance”). The codes were then clustered into nine themes (e.g.,
“Caseworker assistance in problem capture”,“Contextual followups for
teachers”, “Expert Clarifications”).

###  3.5. Ethical Considerations

Our work took place in a fraught and sensitive context: low-income schools in
India. Thus, we took steps to safeguard our participants, especially teachers.
During onboarding, we sought consent both online, when teachers approached the
helpline, and in-person, when caseworkers approached teachers. This ensured
that teachers were aware of any risks associated with using the helpline.
Protecting privacy and confidentiality was also of paramount importance in our
deployment. All stakeholders, including caseworkers, facilitators, and experts
engaged in a short course on (1) what privacy and confidentiality means, (2)
handling different data types (e.g., personally identifiable data) and (3)
best practices for providing support (e.g., how to ensure safe spaces for
teachers to share their issues).

In addition, we took the confidentiality of the case file seriously. Teachers
were assigned a pseudonym. Caseworkers were instructed to not record any form
of personally identifiable information, such as school name, peers, and higher
management names. Facilitators verified the case file before it was shared
with experts. Caseworkers explained these practices to teachers when they
initiated the first conversation with them. If a teacher sought multiple
rounds of support, we ensured that the same caseworker was assigned to them.

##  4\. Findings

Figure 3. Table showing an overview of different types of problems and
associated social support provided to the teachers. PF = Problem-focused, EF =
Emotion-focused support

A graphic table showcasing a summary of different problem categories captured
by saharaline. It also depicts teacher count, common categories of support
provided along with prominent examples and experts involved.

Saharaline was active for three months. During this period, 28 teachers
reached out to the helpline and sought multiple rounds444One round is a full
iteration of steps 1-7 as shown in Figure 2 of social support for different
work stressors. This represented a significant proportion (30.12 %) of the
workforce in the six schools where Saharaline was promoted. At a high level,
our findings show that Saharaline’s collective social support approach
effectively motivated teachers to share a wide array of problems impacting
their occupational well-being. Figure 3 shows an overview of the problems that
the teachers shared. They reflect the most common types of problems teachers
in low-income schools faced in the Global South over the years (Cannanure et
al., 2020b; Gavade et al., 2023; Singh et al., 2023; Bold et al., 2017). Our
findings also show that the collective efforts of the caseworkers and the
experts to provide support were effective as teachers requested an average of
three rounds of support with Saharaline.

In the following sections, we unpack our findings and discuss participants’
experiences providing and receiving hybrid collective social support through
Saharaline. Section 4.1 sheds light on the conversations between teachers and
caseworkers in the process of capturing teachers’ problems. Section 4.2
focuses on the co-production activities between the experts, caseworkers, and
facilitators as they worked together to solve teachers’ problems. Finally,
Section 4.3 focuses on the caseworkers’ efforts in delivering solutions to the
teacher, and the teachers’ subsequent feedback. All participant names are
replaced with pseudonyms to ensure anonymity.

###  4.1. Capturing Stressors: Problem Stories & Scenarios

####  4.1.1. Teachers’ Motivations for Seeking Support

Two types of teachers contacted Saharaline. The first type (n=17) were
explicitly aware of the nature of their problems and could narrate them by
identifying the source of their stressors. They could also describe the impact
the stressors had on their work lives. By sharing their narratives, they
sought targeted solutions for their stressors. Common problems expressed by
explicitly aware teachers included impending deadlines (e.g., syllabus
completions), stressful events (e.g., exams), classroom management,
preparation, and teaching assistance. One example conversation555Emoticons are
omitted from chats to focus on readability between Gita, a social studies
teacher, and Saharaline is presented below:

  * 4:41 PM. Gita: Hello. Are you there? I am Gita
4:41 PM. Saharaline: [Automated welcome message (See Figure 4.A)]
4:50 PM. Representative:  Hello, Gita teacher. Thank you for reaching out to
Saharaline
4:50 PM. Representative: [Template message asking for demographic details and
the issue]
5:29 PM. Gita: [Omitted Demographic details]
5:29 PM. Gita: Do you help with parent issues? I have a P.T.A. meeting in two
weeks and the parents for a few students are not happy.
5:32 PM. Gita: It is becoming very stressful thinking about how to handle
them.

Like Gita, teachers in this category found it easier to establish trust,
clearly narrate problems, and request assistance.

The second type of teachers (n=11) that contacted Saharaline were implicitly
aware of their problems, but found it difficult to identify their stressors
and narrate how the stressors were impacting their work lives. They contacted
Saharaline to express their curiosity about the helpline, share their lived
experiences in schools, and ask broad questions to make sense of their work
lives. Common problems within this category focused on emotional distress
experienced at work, subsequent fatigue and burnout, issues with their
professional image, and the impact of personal struggles on work. Less common
issues included relationship complications with higher management and peers.
Prerna, a Hindi teacher who reached out to Saharaline, shared the following in
a post-support interaction:

  * “When I first reached out to your helpline, I was not even sure why I was messaging you or what I wanted to talk about. At that time, I was just feeling mentally tired and just the thought of going to school was making me want to run away …I still remember, I just messaged because the helpline for teachers made me curious. I never heard of something like this [Saharaline] …Later when I was answering Asmeen’s [caseworker] questions I realized that the management was giving unrealistic amount [of work] …I was also just not interested in doing teaching anymore …But I thought it was my mistake and I was just feeling guilty about it.”

Teachers in this category also found it challenging to articulate their
problems with their peer networks. Saharaline, being an independent
intervention outside their school ecosystem, provided a viable alternative to
seek support. Unlike explicitly aware teachers, they did not have clear
expectations and agendas when approaching Saharaline. As a result, these
teachers shared abstract narratives, which meant that caseworkers had to put
in more effort to surface and capture concrete problems for Saharaline to
assist.

####  4.1.2. Validating & Capturing Problem Stories

Regardless of the teacher’s motivation type, caseworkers contacted the teacher
and captured their problems. To lower the threshold to share problems,
caseworkers encouraged teachers to start with their recent lived experiences.
Caseworkers referred to these narratives as teacher stories.

To surface these stories, caseworkers shared how they had to plan the first
interaction with the teacher carefully. To create an empathetic and positive
first impression, they carefully considered the medium of communication
(WhatsApp message/call vs. in-person conversation), time of communication
(school hours/breaks vs. after-school), environment (inside school vs. outside
school), and motivation of the teacher (explicitly vs. implicitly aware).
Minu, one of the caseworkers, shared some of her considerations while deciding
what medium of communication she had to use when she interacted with teachers
for the first time:

  * I have actually worked with teachers from these communities before. Teachers are quite apprehensive when approached through WhatsApp or any other technological platform. If they are apprehensive, how will they open up? Moreover, interaction via online platform does not help us know what emotional state they are in that day …see their facial expressions …. My first long interaction is always offline to observe all of this while I try to find their problems …we can easily connect this way. But I never force them. Ultimately, they choose.

.

Generally, our analysis revealed that caseworkers who showed more flexibility
while engaging with teachers received more engagement from teachers.

Figure 4. Message excerpts from helpline; (A) Automated greeting message when
teacher reached out to Saharaline; (B) Caseworkers requesting teacher for
additional context for her problems by asking her to share sample home work
she shares with the students after school & teacher sharing materials in
response; (C) An example of how caseworker localizes the expert solutions from
the case file. The first snippet introduces the teacher to mindful meditation
techniques and the second snippet shares important helpline numbers and
introduces the notion of a “help friend”; (D) Curated summary for experts.
Message consisted weekly highlights, teacher and caseworker’s feedback; (E) A
teacher sharing a video of her executing suggested solutions in the classroom
by the expert.

Five sample WhatsApp message excerpts shown from the helpline. First image is
the automated greeting message when teacher reached out to Saharaline. Second
message depicts caseworkers requesting teacher for additional context for her
problems. Third image shows an example of how caseworker localizes the expert
solutions from the case file. Fourth images depicts curated summary for
experts consisting weekly highlights, teacher and caseworker’s feedback. Final
image shows a teacher sharing a video of her executing suggested solutions in
the classroom by the expert.

####  4.1.3. Translating Problem Stories to Problem Scenarios

The stories shared by teachers were extremely rich in detail. Caseworkers
found it ineffective to share them in their original state with Saharaline
experts for solutions. Instead, the caseworkers used different nudges to
encourage teachers to reflect on their stories, extract essential information,
and create concrete scenarios, which they then could register in the case file
for experts.

The caseworkers used scoping questions as a common technique to narrow down
the exact stressors in the teachers’ stories. For instance, when caseworker
Abdul met Ragini, a secondary school Science teacher, her story revolved
around how her class students had become extremely unruly and unmanageable
post-pandemic, because of which she was not able to complete her curriculum,
contributing to stress. While it was clear to Abdul that the teacher was
struggling with classroom management, he still reached out to her on WhatsApp
and asked follow-up questions to narrow down the specific aspects of
management she was struggling with:

  * 10:31 AM. Abdul: Ragini Maam, yesterday, you told me you struggle with controlling children in the classroom. Once the period starts, between when you step into the class and when you come out, what times are the most difficult?
10:33 AM. Abdul: Your answer will help me share exact issues with the expert.
If you are busy, please leave a message
10:33 AM. Ragini: The main problem is making them sit quietly and behave. That
itself does not happen
10:39 AM. Ragini: [Voice message in which Ragini shared an example of how
students talk among each other and how she took 20 minutes to silence the
class and start the lesson]
[Abdul asked a few follow-up questions]

Based on the conversation, Abdul created a concrete problem scenario
indicating that Ragini struggled with classroom management strategies,
particularly in setting clear expectations and modeling ideal behavior.
Another strategy used by caseworkers was to nudge teachers to consider the
relative impact of the problems on their work lives. Caseworkers shared how
some teachers reported several problems at once in their stories. To
effectively support them, the caseworkers assisted the teachers in
understanding, ranking, and prioritizing problems that affected their well-
being the most. Based on teachers’ responses, caseworkers broke down the story
into multiple scenarios and prioritized the scenarios.

Caseworkers also nudged teachers to provide additional contextual information
to their stories that could uniquely anchor their problems to their local
settings. For example, caseworkers requested supporting materials to make the
scenario as concrete as possible. Our analysis revealed that caseworkers
included all kinds of supporting materials, including documents like book
chapters, the curriculum schedule of the school, and detailed descriptions of
students present in teachers’ narratives. They complemented this effort by
including passive indicators they observed in person while listening to the
teacher’s problems, such as environmental, social, and infrastructural
details.

For instance, Harpreet, a caseworker, was assisting Parnita, who was teaching
Mathematics to secondary school students in a remote school. Post-pandemic,
their school had adopted a hybrid approach to teaching. Due to pressure to
complete the syllabus, Parnita was instructed to teach half of the curriculum
at school and send notes for the other half via WhatsApp to students’ parents.
However, there were three students whose families did not have phones or
Internet access. The teacher was extremely stressed and reached out to the
helpline. While producing tangible problem scenarios, Harpreet included in-
depth details of the three students, including their parents’ occupations,
other fellow students’ families in the vicinity, pictures of student
neighborhoods, and internet cafe and photocopy shop availability. Esha, a
teacher trainer and a pedagogical expert, shared how these details were
invaluable in designing peer-based activities by including the student’s peers
who lived near his house.

In another example, caseworker Minu shared how one of the teachers needed
content and pedagogical tips for a specific chapter. To provide context for
the expert, she took a photocopy of the book chapter, annotated the issues
across the margins, took a photo, and shared it with the helpline. The
caseworker then submitted the problem scenarios to the helpline by recording
them in the case file. In instances when their support overlapped with
multiple teachers, caseworkers optimized their time to submit the information
by sharing photos of handwritten notes or voice notes on WhatsApp with the
helpline facilitators who transcribed, formatted, and appended the scenarios
to the case file.

####  4.1.4. Caseworker’s Challenges In Capturing Problem Stories and Creating
Problem Scenarios

Crafting problem scenarios that encapsulated teachers’ stressors was
complicated for caseworkers despite their familiarity with teachers’ work
environments. For instance, caseworkers found it more difficult to surface
stories from teachers who were implicitly aware of their problems. All
caseworkers unanimously shared how they had to spend more time with the
implicitly aware teachers. They had to engage in alternative strategies that
allowed them to obtain the stressful themes in the teachers’ lives
organically. Harpreet shared how her first interaction with a teacher who
contacted the helpline out of curiosity was to meet and initiate a general
conversation about herself. These unrelated and open-ended conversations
allowed the teacher to open up and share their stories. Harpreet shared:

  * “Once he opened up with his stories, it was much easier for me to ask follow-up questions and understand where he was stressed. [This] teacher was mentally burned out but did not come to terms with it …his stories gave away those issues. I suddenly came up with this idea. I told him that we at the helpline are sharing 10-min video prompts that are around different work topics, teachers just see them and I come after a few days and we talk about it …helpline [facilitator] said they could do something like this with the experts …Mental health for teachers was one topic …Guess what topic the teacher chose? Mental health.”

The idea of such small prompts was effective with implicitly aware teachers as
they acted as catalysts for teachers to open up for more conversations with
the caseworkers. However, in a few instances (n=3 who needed emotion-focused
support), caseworkers asked the helpline facilitators to connect them directly
with the experts. When the caseworkers went back to interact with the
teachers, they put the expert on the call so they could ask focused questions.
Answers to those questions helped caseworkers shape scenarios they found
difficult to do independently.

Another challenge for caseworkers in having meaningful conversations was
working around teachers’ lack of personal space and time in the work
environment. All low-income schools that the caseworkers visited had limited
real estate for classrooms and staff rooms. It was common for teachers to
shuffle between an empty classroom and an unoccupied staff room as the rooms
saw constant movement from students and teachers. Moreover, when other
teachers saw a particular teacher engaging with the caseworkers in serious
conversations, they gathered around the teacher and steered the conversation
away from the particular teacher’s concerns. This practice complicated the
caseworker’s effort to create scenarios mapped to the concerns of the teacher
who reached out to Saharaline for support. To overcome this issue, several
teachers (n=11) requested caseworkers to meet outside their school, such as
makeshift playgrounds in front of schools and public spaces near schools, to
maintain privacy.

###  4.2. Clarifications, Development, & Refinements: Problem Scenarios to
Solution Scenarios

####  4.2.1. Experts’ Clarifications to Produce Solution Scenarios

Once the caseworkers added the problem scenarios and relevant supporting
information to the case file, the facilitators assigned them to the experts.
Based on the stressors mentioned in the problem scenario, a single teacher was
mapped to one or more experts in parallel. After reading the case file, if
experts needed clarifications and additional context before developing
solutions, they were encouraged to interact with the caseworker through the
helpline.

Our findings suggest that experts appreciated this layer of separation for a
few reasons. Experts shared that, by choosing to distance themselves from the
process of problem formulation and context development, they could devote more
time to finding meaningful solutions for teachers’ problems. This allowed
experts to scale their support by working on multiple cases simultaneously.
Pedagogical expert Esha shared:

  * I like to have some emotional distance from the teacher for whom I am providing a solution while having a way to get more information. Being remotely available through this kind of app service is perfect …Don’t get me wrong. The reason I say this is because my job is not just to provide a solution that reduces stress for that one teacher, but to do justice to all teachers equally. Abdul’s [caseworker’s] job is a really satisfactory one, but if I am doing that too and engaging with teachers …teachers’ lives are so challenging and stressful that I cannot move beyond that first teacher.

When needed, experts reached out to the helpline for additional
clarifications. In total, we recorded 128 requests for clarifications raised
by experts. On average, this amounted to two clarifications per solution
provided to a teacher. Within these, an essential type of clarification sought
by experts was technical specifications related to their field of
specialization. Common examples included teachers’ pedagogical strategy (e.g.,
student-centered learning), curriculum details (e.g., national or state
curriculum), professional development certification details (e.g., state-
sponsored or support organization sponsored), and technological configurations
(e.g., availability and the resolution of the projector).

Another type of clarification sought by experts pertained to potential
conflicts they anticipated their solutions could introduce into teachers’ work
lives. They shared three distinct scenarios. One possibility was that their
solutions could conflict with the school-specific norms imposed by school
management. Another concern was that their solution could conflict with other
problems faced by the teacher that were not yet added to the case file.
Lastly, they were also concerned that their solutions might conflict with
those provided by other experts.

In all situations, the experts requested additional information to ensure
their solutions did not create further distress when teachers implemented
them. One such instance occurred when Sunita, a Science teacher, contacted the
helpline to express her stress stemming from interactions with students’
aggressive parents. In the problem scenario, the caseworker explained that due
to a significant decline in students’ learning levels following the pandemic,
the school had directed teachers to revisit the previous year’s syllabus. This
decision was met with resistance from parents, who harassed and accused the
teacher via WhatsApp of not letting their children progress. Sunita was
understandably distressed, as she felt she was doing everything she could to
educate the students. In response to this problem scenario, Jayanth, the
pedagogical expert assigned to this case, wanted to share activities that
Sunita could distribute to parents via WhatsApp to alleviate some of her
pressure. However, Jayanth sought clarifiation before providing the solution
as their solution conflicted with that of Priti, the occupational mental
health expert:

  * 9:23 AM. Jayanth: Hi…. I just saw Priti ma’am’s [mental health expert] solutions. There is a slight issue.
9:24 AM. Jayanth: She thinks the parent’s harassment is causing stress to
Sunita [teacher]. She mentioned some strategies to help her handle them, which
is good……
9.26 AM. Jayanth: One suggestion she shared is to stop interaction for a few
weeks and ask the principal to intervene till she feels better.
9.28 AM. Jayanth: …. I designed a few exercises for Sunita to involve parents
in their children’s learning for the syllabus they wanted the teacher to
teach. My goal was to help teacher give some homework that could be done by
parents and students together.
9.30 AM. Jayanth: But I don’t want to unnecessarily confuse the teacher by
giving contradictory instructions. Can you confirm with Priti ma’am and let me
know what she thinks?
9.39 AM. Jayanth: If she thinks its not okay….. I will probably add a note or
just come up with something else… I have left comments for her on the case
file for clarity

####  4.2.2. Refining the Solution Scenarios

Once the expert received clarifications, they developed a rough draft of the
solution and added it to the case file. Experts called these solution
scenarios, mirroring caseworkers’ use of problem scenarios. A typical draft of
a solution scenario comprised three parts. The first contained the reasoning
behind the teacher’s problem (e.g., “you [teacher] are facing this fatigue
because you are not able to say NO to the management certain situations”),
followed by contextualized instructions for the teacher (e.g., “explain to the
teacher that improving learning levels of students will take time”), and
ending with supporting audiovisual materials that showed the implementation of
the suggested instructions in a contextual scenario (e.g., hand-drawn image of
a leader board system for high school students to encourage increased
productivity and thereby learning levels). After adding a draft solution
scenario, the expert sought another round of clarifications from caseworkers
to refine and finalize their solutions.

Caseworkers used this opportunity to share their perspectives on the
practicality, the resource requirement, and any additional burden the proposed
solutions could create on teachers. In a similar issue with parents for
another teacher, Romila, another expert, suggested the teacher document her
work with the students as proof to show the parents. The caseworker pushed
back against the suggestion by reasoning that written documents could add to
the teacher’s current documentation burden in school. Instead, the caseworker
suggested the creation of one minute video logs (similar to YouTube Shorts) of
their classes to achieve the same objective with less work.

Experts also sought explanations to refine their solution scenarios based on
the caseworker’s understanding of whether the teachers had tried prior
strategies to address their stressors. To confirm this, they requested the
caseworkers to provide details of any steps the teachers took as part of their
efforts. These requests comprised the biggest proportion (approx. 38%) of the
overall clarifications sought by the experts. Based on this feedback, experts
refined their solutions and proposed more effective strategies. The high
frequency of these clarifications motivated caseworkers to include this
information as contextual information within their problem scenarios.

In total, we found that experts created 79 solution scenarios throughout the
deployment period, comprising five different types of social support (see
Figure 3). The most common and least common types of support provided were
informational support, a type of problem-focused support (Carroll, 2020) where
information is provided on ways to reduce stress (72%), and network support, a
type of emotion-focused support where network connections are provided to
manage the emotions, rather than altering the situation (6%). In the finalized
solution scenarios, the experts also added instructions for caseworkers to
share the solutions with the teachers. These explanations added a layer of
assistance to the instructions meant for teachers, especially for those
solution types that the experts thought were unfamiliar or tricky to follow.
Moreover, when experts realized that the teacher’s strategies for problems
were ineffective and detrimental to their well-being, they also instructed the
caseworkers on how to inform teachers about it. For example, the mental health
expert Priti, shared the following instructions to the caseworker in the
teacher’s solution scenario:

  * “The teacher’s idea regarding partitioning the dull students and giving them more importance is a good idea but please make her understand (when she is alone) that doing it in front of the bright students might create a feeling of resentment/dislike towards the teacher and [the students might] become disinterested with the subject. It will unfortunately only add to the problem for which the teacher reached out in the first place and make her more stressed.”

To help experts add their solution scenarios to the case file on time, the
facilitators provided recurring alerts and periodic reminders of clearly
articulated deadlines based on the caseworker’s subsequent scheduled visit to
the school. When the experts required more time, they contacted the
facilitators to keep them informed. In those cases, caseworkers had to
reschedule their appointments with the teacher accordingly. In the entire
study, there were four such instances where experts requested extensions.

###  4.3. Delivering Solutions & Follow-ups: Solution Stories

####  4.3.1. Strategies and Challenges

Once experts finalized the solution scenarios, caseworkers shared them back
with teachers. However, caseworkers felt the solution scenarios in their
original form were dense in information. Consequently, all the caseworkers
simplified the scenarios to increase the teachers’ understandability and the
subsequent likelihood of implementing the solution in their work lives.

One simplification strategy was to familiarize themselves with the solution
scenario and express them as a series of illustrated snippets through WhatsApp
(see Figure 4. C). Caseworkers referred to the snippets as “solution stories”.
They sent these stories a few hours before interacting with the teacher to
invoke curiosity towards the solution. The story illustrations were either
sourced from the supplementary materials in the solution scenarios or curated
separately through online searches to localize the solutions to teacher’s work
settings.

In some cases, caseworkers took an additional step by demonstrating to
teachers how to implement the solution stories, with the hope of invoking
discussion. To do this, caseworkers either met the teacher in person or
recorded themselves demonstrating the activity. For instance, Suman, a
secondary school Science teacher, contacted Saharaline about class management
issues. She described how the caseworker, Asmeen, visited and demonstrated
strategies:

  * “Asmeen was very patient …After school, we sat in a classroom and discussed my issues. She has seen me teach. So we imagined that the classroom had students and he showed me some management techniques. I am actually a new teacher and she is familiar with my students. So after she showed me I asked her, “what about [student name]. He will get too excited and disrupt the class?!” and then she replied what to do in this new situation …This exchange was helpful …One time I had to record her solutions because I was in hurry …I am so tired at the end of the day. It is morally uplifting to see someone sitting with you and then working through your problems. ”

Through these strategies, caseworkers aimed to make solution scenarios easily
understandable for teachers. The demonstrations encouraged teachers to
implement the solutions by reducing barriers, such as hesitation or
embarrassment. Caseworkers’ physical presence also encouraged teachers to
actively resolve any follow-up questions.

Despite the strategies, caseworkers experienced several challenges while
delivering solutions to the teachers. A key challenge was convincing teachers
to implement emotion-focused solutions to manage the negative emotions
associated with stress rather than altering the stressful situation or
eliminating the stressor. For instance, Sofia, a young teacher with six years
of teaching experience, reached out to the helpline with issues of burnout at
work, loss of interest in teaching, and a desire to discontinue the job. She
felt like she was “stuck and could not do anything about it”. The caseworker,
Abdul, was responsible for sharing self-care activities, such as recognizing
negative thoughts about her job and trying to transform them into positive
ones (referred to as cognitive restructuring (Clark, 2013)). It took multiple
visits by Harpreet to persuade the teacher that these activities would have
long-term benefits.

Another challenge in delivering solutions was that it took around seven days
to provide a complete round of social support (steps 1-7 in Figure 2). By the
time caseworkers returned with solutions, teachers had implemented their own
solutions on a few occasions (n=4). In such cases, case workers had to report
these new solutions to Saharaline and confirm the applicability of the expert
solutions in light of the teacher’s own solutions. If the expert suggested
changes, the updated solutions were shared with the teacher. On certain
occasions, teacher’s own support efforts contributed to additional stress
rather than relief. In those situations, caseworkers had to make a substantial
effort in convincing teachers, especially with seniority, to discontinue such
practices. For example, two teachers reached out to Saharaline, sharing how
they were experiencing harassment from senior teachers in the school. As a
coping strategy, they stopped engaging with all of their peers, including
essential activities such as teacher development training and parent-teacher
meetings. Caseworkers had to first work with the teachers to help them
recognize and stop their detrimental coping mechanisms before they could
suggest new activities proposed by the expert.

On rare occasions, caseworkers, due to their neutral position in the school
ecosystem, became an active part of the solution for problems involving power
dynamics or persistent systemic issues. In such instances, experts encouraged
caseworkers to strategically approach management and increase the visibility
of systemic issues on behalf of teachers. Caseworkers shared how they had to
conduct these conversations carefully, keeping teachers’ identities anonymous.

####  4.3.2. Factors Determining Teacher’s Solution Adoption & Follow-up
Support

Our data show that teachers, on average, availed three rounds of support (min=
1, max = 7) from the helpline. The subsequent rounds of support were either a
follow-up of the same problem or a new problem. While the data suggest that
the teachers found Saharaline to be beneficial for longitudinal support, it is
important to understand what factors teachers considered to implement a
solution and even request follow-up support.

An essential factor was the priority of the problem in the teacher’s life.
Saharaline support took anywhere between four and seven days to provide a
solution to the teacher’s problem. On occasion, between the time when the
teacher shared their problem and when the caseworkers shared the solutions,
other higher-priority problems took precedence. On such occasions, the teacher
either put the implementation of the suggested solution on hold or used the
follow-up visits to address the higher priority problem. A teacher shared one
such example:

  * “ Yes, Asmeen [caseworker] had shared the solution for the new [student-centered] teaching method that the [principal] sir was asking from me. We had one conversation about what to do for my sandhi-vicchhed [a grammar topic in Hindi] chapter. But I could not implement them because exams were scheduled a week earlier all of the sudden. I had a completely different problem then. I needed help in tackling students with different learning skills who were not able to grasp the concept and I was stressed about completing the syllabus. I requested Asmeen to help me with some techniques in completing the hard to grasp lessons to finish the syllabus that is appearing in this exam.”

Another factor teachers considered while incorporating the solution was the
perceived amount of effort necessary to implement the solutions and the time
required to see the results. Teachers were more likely to try a solution if
the caseworkers broke it down into comprehensible pieces and clearly
demonstrated its feasibility.

The likelihood of follow-up questions was also determined by perceptions
around how much effort would be required to incorporate solutions. When
teachers found it easy to implement the solutions in their work lives and
perceived the results as effective, their trust in Saharaline increased, and
they reached out for subsequent assistance. We also saw the likelihood
decrease when the caseworker shared solutions in a delayed manner. Among the
teachers who took subsequent rounds of support from Saharaline, eight teachers
requested additional support for the same issue, four teachers shifted to a
new problem, and fourteen requested for both. Interestingly, caseworkers also
initiated a few follow-ups in certain circumstances when they felt that the
teachers were showing symptoms of stress, such as melancholic status messages
on WhatsApp or when they heard distress updates from other peers.

During the follow-ups, caseworkers also sought feedback from teachers on the
provided solutions and shared it with the facilitators.  Interestingly,
facilitators revealed how they realized that the initial Saharaline’s design
lacked appropriate structures to inform experts about the teachers’
experiences for whom they provided support. To address this issue,
facilitators devised the idea of gamified weekly summary prompts, which they
shared on WhatsApp. These prompts contained updates on delivered solutions,
such as the count and category of solutions the expert shared the previous
week and a sentence summary of the feedback from teachers and caseworkers (see
Figure 4.D).

####  4.3.3. Perception of Saharaline

We now briefly discuss the technological experiences of caseworkers, experts,
teachers, and facilitators. All stakeholders unanimously shared that the
choice of everyday technologies like WhatsApp was helpful for easy adoption
and seamless use of the platform in receiving and providing social support.
This was a key factor because all the stakeholders were on a tight work
schedule during their work hours, and they greatly appreciated not having to
learn a new technology. Pushpa, one of the experts, shared her perspective on
this matter:

  * “One good thing about using WhatsApp was that it was easy to go back and forth because sometimes a question suddenly comes to mind while working on the solution or cooking. It is easy to go back and check: will this work for that teacher? Regarding accessibility, I felt a lot more comfortable and I am glad it was on WhatsApp and not on a new app I have to learn. I already use so many custom apps for this and that. …”

However, a few teachers also shared (n = 5) how interactions on WhatsApp added
to the already overwhelming number of messages they received. These teachers
indicated a strong preference for in-person interactions. By contrast,
experts, who were comfortable with technology use, requested an option to seek
additional review from another expert as a second pair of eyes to increase the
veracity of their solutions. Lastly, they shared how, as teachers requested
more follow-up support sessions, it took substantial work to cross-check older
WhatsApp clarifications with the case file and make connections. Instead, they
preferred a copy of their message interactions added to the case file to
maintain prior context of the problem in the same file where they provided the
solutions.

##  5\. Designing for Improved Collective Social Support

Our findings show that Saharaline surfaced a wide range of teacher issues and
support needs. Here, we reflect on our findings, discussing the benefits and
tensions of Saharaline’s highly versatile approach to delivering collective
social support (Section 5.1). We also highlight how Saharaline’s design
enabled decentralized production of knowledge, which improved the overall
distribution of expertise and resources (Section 5.2). Finally, we reflect on
our choice to deliver collective social support via WhatsApp, itself often a
stressor for teachers (Section 5.3).

###  5.1. Versatility of Collective Social Support Practices

In low-resource settings, disparities in school infrastructure and resources
lead to significant differences in teachers’ local work practices (Cannanure
et al., 2020b; Alcott and Rose, 2015) (e.g., the curriculum they follow,
language of instruction, available infrastructure, and access to professional
development). Saharaline caseworkers effectively captured these local
practices, along with the teachers’ problems, particularly benefiting
implicitly aware teachers who struggled to articulate their issues. Experts
then combined this local information with their cross-cultural knowledge,
which included domain expertise and deep understanding of the Indian education
system. This collaborative effort produced contextual solutions that
caseworkers and teachers could readily implement in local contexts.

Collective social support was effective due to this inter-dependency between
localization practices (by caseworkers) and theory-driven practices (by
experts) to provide balanced support. Caseworkers and experts carefully
negotiated their inter-dependencies for different types of support. When
Saharaline provided problem-focused social support, the team’s inter-
dependencies were well-defined, relatively simple, and mainly carried out on
WhatsApp. These observed patterns align with problem-focused support in
collaborative care environments, akin to monitoring health measurements
through simple technologies and straightforward protocols (Caldeira et al.,
2017). The utilization of uncomplicated technologies facilitated ease of
learning, while clear-cut activities promoted improved coordination among
stakeholders, reaffirming Hwang et al. (2020)’s findings. In our study, the
majority of problem-focused stressors, encompassing teaching, preparation, and
administrative issues, manifested as structured problems with systematic
solutions, thereby enabling effective collective social support.

By contrast, when teachers required emotion-focused support, the inter-
dependency between actors increased in complexity, requiring carefully
coordinated collaborations delivered in a hybrid manner. This was because
these issues were often implicit and less structured. Collective support
systems implemented in resource-constrained environments face challenges in
addressing such implicit support requirements. These systems often depend
solely on the collaborative efforts of individuals within the community (e.g.,
parents seeking relatives for educational support (Madaio et al., 2020)) or
external experts who are not part of the community (e.g., researchers
providing expertise in resolving technological issues (Peters et al., 2014)).
This reliance on either community collaboration or external expertise makes it
difficult to fully comprehend implicit support needs. In our study, we
identified a middle ground by empowering caseworkers, who possessed local
awareness, to bridge the gap and connect with experts. early in their
communication with teachers to better capture these implicit requirements and
improve the problem scenarios they developed (Section 4.1.4). Similarly,
experts requested clarifications from caseworkers when suggesting solutions
(Section 4.2.1). This versatility in inter-dependency enabled Saharaline to
effectively handle a wide range of both known and new issues, while keeping
the burden for the system and individual roles low (Archer et al., 2012).

However, the versatility of the support may have come at the cost of the time
required to provide it. Our findings show that it took an average of six days
for the Saharaline team to provide support. Caseworkers consumed most of this
time (roughly four days) to establish connections with teachers, build
rapport, and capture their local experiences and problems. Experts took
roughly two days to craft solutions, and facilitators took a few hours to
coordinate the overall process. In a few time-sensitive cases (n=3), by the
time the Saharaline team delivered solutions, new, higher-priority problems
had surfaced in teachers’ lives (Section 4.3.2). In such situations, teachers
put the original problem and associated solutions on hold, and either picked
them up later or never tried them.

Another challenge was that Saharaline relied heavily on the role of
caseworkers, who were the key stakeholder that interfaced with the teachers.
Success of personalized case management systems rely on these actors who can
build rapport, and encourage reflection and discourse (Tseng et al., 2022).
This study adds to this criteria wherein caseworkers also carefully separated
their role of problem translators (“emotion”) from the experts (“technical”)
who solved the problem by establishing clear boundaries, something that prior
research found challenging (Tseng et al., 2022). But this also means that the
intervention relied on low-income schools having caseworkers already deployed.
This might not be always the case with all low-income schools. In such cases,
support organizations need to play a critical role in helping schools train
caseworkers from the local community that occupy a similar neutral position.
More research is needed to understand how such interventions can be deployed
and sustained in low-income schools that lack easy access to support
organizations and their deployed roles.

These findings highlight a tension in providing collective social support to
teachers. On one hand, receiving personalized support and expert-crafted
solutions from domain experts within a week (i.e., six days) may be considered
a fast turnaround for such a service. Indeed, our goal in designing Saharaline
was to deliver longitudinal support to teachers over long periods of time, not
to run an emergency service. On the other hand, some teachers’ priorities
changed before Saharaline could provide support. Given this, a logical
solution may be to try and provide support more rapidly. However, we would
caution against the assumption that faster support would be better. Taking
time to build rapport and deeply understand teachers’ contexts, and carefully
considering potential repercussions of any provided solutions on teachers’
lives, are important steps that necessarily take time. As such, “fast-tracked”
solutions may run the risk of harming the target populations and exacerbating
their problems (Madaio et al., 2020). Instead, researchers deploying such
collective social support in the future should carefully consider if workers
will need time-sensitive or urgent support and plan accordingly. In
Saharaline’s case, most teachers who reached out for support did so for non-
time-sensitive problems, and appreciated Saharaline’s approach to providing
personalized, localized assistance via multiple rounds of support.

###  5.2. De-centralized Knowledge Production

Saharaline’s versatile design involved experts from multiple support
organizations, thereby enabling decentralized knowledge production that was
culturally and socially diversified. Such diversified, decentralized support
systems function as a robust source of alternative knowledge for teachers
(Pendse et al., 2022; Mignolo and Walsh, 2018). They play a crucial role in
raising awareness and addressing sensitive topics, (e.g., mental health),
which might be considered taboo and not addressed by centralized support
systems governed by management. Here, we further unpack this decentralized
form of knowledge production.

When teachers contacted the helpline, they shared stories containing tacit
knowledge gained over years of teaching. This knowledge encompassed implicit
practices related to classroom and community culture, student behaviors, and
commonly encountered challenges. Shulman (1986) defined such forms of applied
tacit knowledge as pedagogical content knowledge. Caseworkers then translated
these stories into explicit, declarative knowledge scenarios, incorporating
language and references that reflected the technical background and skills of
the expert. In documenting scenarios, caseworkers assumed the role of active
knowledge translators, systematically organizing scenarios and adding context.

The experts, in turn, analyzed the problem scenarios using their conceptual
knowledge of mental health, pedagogy, and educational technology. They used
this knowledge to evaluate the problem severity and generate recommendations
in the form of solution scenarios. These contained solutions for teachers
alongside, more importantly, instructions for caseworkers in the form of
procedural knowledge. As such, experts served as knowledge providers.
Caseworkers then again assumed the role of knowledge translators, taking the
relevant instructions from the expert’s solution scenarios and localizing them
to suit the teacher. As translators, their task involved simplifying concepts
into a language comfortable for the teacher within their community.
Decentralization of roles also facilitated knowledge production at multiple
steps involving multiple roles. Saharaline’s design successfully distributed
these knowledge production efforts, enabling the system to be approachable for
teachers, while being managable to carry out by stakeholders.

For their part, facilitators played an essential role in ensuring the
timeliness of knowledge production and the seamless transfer between
caseworkers, experts, and teachers. These activities can be categorized into
two types of tasks. The first are coordination tasks that facilitators engaged
in to ensure the helpline was functioning as expected (e.g.,connecting
teachers with caseworkers, routing clarifications between experts and
caseworkers, and rescheduling interactions between caseworkers and teachers
when an expert’s solutions was delayed). These tasks also involved translating
between different languages (Hindi, Kannada for caseworkers and English for
experts) to enable conversations. The second type of task revolved around
information management, which encompassed information collection,
organization, and communication at various levels. These tasks included
capturing caseworkers’ audio and textual notes in the case file, mapping
appropriate experts to the case file based on the problems shared, weekly
information synthesis of details of the support provided, and sharing gamified
prompts with the experts.

Facilitators’ efforts, while simpler than knowledge production tasks
undertaken by caseworkers and experts, consumed a lot of time and energy to
ensure smooth functioning of Saharaline. We see opportunities for research
that explores how to reduce facilitators’ workload and enhance the scalability
of collective social support efforts through conversational agents capable of
augmenting facilitator responsibilities. We draw on literature on human-AI
collaboration (Grudin and Jacques, 2019; Jiang and Ahuja, 2020), which posits
that humans and conversational agents have different strengths and limitations
in online activities. Complementing the strengths of facilitators with those
of conversational agents could enable expansion of the collective social
support system. For example, extending the asymmetrical design (Rahman et al.,
2021), conversational agents could effectively assist facilitators with
information management tasks, while routine coordination tasks (e.g.,
translation and nuanced communications) are done by facilitators. One approach
to facilitate this collaboration would be implementing the conversational
agent on top of WhatsApp through their API. Conversational agents could
propose automated responses based on teacher, caseworker, and expert requests.
Facilitators would have the option to either choose the agent’s response or
craft their own.

###  5.3. Hybrid Collective Social Support & Technostress

Saharaline’s collective social support intervention utilized smartphone-based
WhatsApp. However, a major stressor in our findings (and in prior work
(Varanasi et al., 2021b)) is technostress. Here, we discuss the impact of
deploying a support intervention using the same technology that was also a
source of stress for teachers. In our intervention, teachers had the option of
receiving support either through WhatsApp or in person. In our findings,
several teachers chose to interact and receive support in person , while also
receiving assistive information (e.g., support materials) through WhatsApp. We
postulate that an important rationale behind this strategy was to safeguard
themselves from the perceived stress associated with the excessive use of
WhatsApp and other personal apps for work purposes. Ayyagari et al. (2011)
classifies this form of stress as techno-overload. Enabling teachers to have
conversations about their problems in person is what made Saharaline truly
hybrid as, at any given point, Saharaline was simultaneously functioning in
offline spaces (between caseworkers and teachers) and online spaces (between
caseworkers, experts, and facilitators).

Additionally, by intentionally choosing offline spaces for conversations,
teachers could control where these conversations occurred. In section 4.1.4
teachers deliberately chose safe or private spaces. This choice gave them a
sense of control and enabled them to keep work-related conversations,
especially about their problems, out of their personal lives. This ability to
control conversations could have been reduced had the caseworkers compelled
teachers to have conversations on WhatsApp, leading to a form of technostress
called techno-invasion (Tarafdar et al., 2019). The overall flexibility and
agency for teachers to control how they received social support influenced
their likelihood of implementing the provided solutions and returning for
further support.

##  6\. Limitations, Future Work & Conclusion

This paper reports on preliminary experiences of implementing collective
social support—a community-centric social support practice—aimed explicitly at
workers in low-resource settings to improve their occupational well-being. We
studied these experiences by designing and deploying Saharaline, a WhatsApp-
based hybrid collective social support intervention that leveraged support
organizations (educational non-profits) operating in low-resource Indian
schools to assist teachers in addressing various stress-inducing challenges.

This study was exploratory and has the usual limitations posed by qualitative
research. To understand the feasibility of the service and the experience of
multiple stakeholders, we kept our sample size of teacher and support
organization staff small. To augment our qualitative findings, we suggest that
future research engage with a larger sample of teachers across a longer period
(e.g., an academic year) to understand the relative duration in teachers’ work
lives where they find collective support helpful. Future studies could also
focus on measuring teachers’ perceived social support and its impact on
different indicators of occupational well-being, such as technostress, work
satisfaction, and burnout, which could further emphasize the importance of
social support services for vulnerable working communities.

While our findings with teachers indicate the effectiveness of collective
social support in their work lives, it is important to understand the impact
of such support on other work practices that fall under the larger umbrella of
emotional labor. Work practices vary greatly between different professions and
specific support practices that are effective for certain professions can be
ineffective for others. Further research could generalize collective social
support practices to improve occupational well-being outcomes across
vulnerable professions.

Lastly, we intentionally designed Saharaline to be simple in its
implementation to understand the fundamental sociotechnical practices
necessary to provide collective social support rooted in local community
needs. Based on these preliminary findings, we plan to study the integration
of a more robust sociotechnical system that leverages mature technological
capabilities (e.g., use of conversational agents) to assist in coordination
(intimating deadlines) as well as knowledge organization (organizing case
files), and synthesizing activities (sharing summaries). Taken together, these
future research directions could establish well-balanced sociotechnical
collective social support practices that can increase the resilience of
vulnerable working communities in low-resource settings.

###### Acknowledgements.

This work was made possible by the generous assistance of various support
organizations. We express special gratitude to Meghshala for their enduring
support throughout our research. We extend our thank you to the teachers who
participated in the study and shared their valuable experiences of using the
intervention. Finally, we also thank the external reviewers for their feedback
on the paper.

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