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Non-Participation in Epidemiological School-Based Surveys: Using Mixed Methods to Study Predictors and Modes of Justification for (Non-)Participation at the School Level

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Title: Non-Participation in Epidemiological School-Based Surveys: Using Mixed Methods to Study Predictors and Modes of Justification for (Non-)Participation at the School Level
Language: English
Authors: Dey, Michelle (ORCID 0000-0002-4300-1877), Marti, Laurent (ORCID 0000-0002-9690-3727), Helbling, Laura Alexandra (ORCID 0000-0002-8310-5427), Jorm, Anthony Francis (ORCID 0000-0002-1424-4116)
Source: International Journal of Social Research Methodology. 2022 25(2):171-182.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 12
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Descriptors: Response Rates (Questionnaires), Student Surveys, Epidemiology, Predictor Variables, Principals, Participation, Foreign Countries
Geographic Terms: Switzerland
DOI: 10.1080/13645579.2020.1864088
ISSN: 1364-5579
Abstract: Response rates in epidemiological studies have generally been decreasing over the past decades. However, when the target group consists of adolescents and young adults, school-based surveys have hitherto been able to mitigate this problem: This age group can be reached relatively easy in the school context (e.g., as compared to reaching them by phone) with very low refusal rates at the student level. However, the present study used a mixed-methods approach and suggests that schools at the organizational level have meanwhile become the problematic bottleneck for school-based surveys, as they increasingly reject requests for study participation. The current article provides insights into promising means for counteracting this trend. Researchers are advised to offer flexible timeframes for schools' participation and to involve institutional gatekeepers who are endorsing their study. Furthermore, researchers, funding agencies, and schools would benefit from joint regional survey coordination systems. Such means will be crucial for the representativeness of future school-based epidemiological surveys.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1341490
Database: ERIC
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  Value: <anid>AN0156163090;9eb01mar.22;2022Apr08.05:55;v2.2.500</anid> <title id="AN0156163090-1">Non-participation in epidemiological school-based surveys: using mixed methods to study predictors and modes of justification for (non-)participation at the school level </title> <p>Response rates in epidemiological studies have generally been decreasing over the past decades. However, when the target group consists of adolescents and young adults, school-based surveys have hitherto been able to mitigate this problem: This age group can be reached relatively easy in the school context (e.g., as compared to reaching them by phone) with very low refusal rates at the student level. However, the present study used a mixed-methods approach and suggests that schools at the organizational level have meanwhile become the problematic bottleneck for school-based surveys, as they increasingly reject requests for study participation. The current article provides insights into promising means for counteracting this trend. Researchers are advised to offer flexible timeframes for schools' participation and to involve institutional gatekeepers who are endorsing their study. Furthermore, researchers, funding agencies, and schools would benefit from joint regional survey coordination systems. Such means will be crucial for the representativeness of future school-based epidemiological surveys.</p> <p>Keywords: School-based; response rate; epidemiological studies; non-participation; nonresponse bias</p> <hd id="AN0156163090-2">Introduction</hd> <p>Response rates in epidemiological studies have been decreasing over the past decades, with particular steep declines in more recent years (Curtin et al., [<reflink idref="bib7" id="ref1">7</reflink>]; Galea & Tracy, [<reflink idref="bib12" id="ref2">12</reflink>]; Morton et al., [<reflink idref="bib28" id="ref3">28</reflink>]). According to Galea and Tracy ([<reflink idref="bib12" id="ref4">12</reflink>]), there are two central reasons for this trend. Firstly, it has become more difficult to reach eligible people (for instance, in telephone-based surveys; Curtin et al., [<reflink idref="bib7" id="ref5">7</reflink>]) and, secondly, people are more frequently asked to participate in (non-)academic research (including marketing surveys, political polls) – eventually leading to a universal reluctance to take part in any kind of survey. This becomes particularly problematic if the decisions not to participate are associated with the study's aim anffd thus potentially leading to a non-response bias (Galea & Tracy, [<reflink idref="bib12" id="ref6">12</reflink>]).</p> <p>In the case of epidemiological surveys targeting adolescents and young adults in the general population, some of the above-mentioned tendencies might possibly be overcome by opting for a <emph>school-based survey approach</emph>. More precisely, response rates at the student level are typically very high in epidemiological school-based surveys around the world (e.g., Jeannin et al., [<reflink idref="bib18" id="ref7">18</reflink>]; Lin et al., [<reflink idref="bib20" id="ref8">20</reflink>]; Morioka et al., [<reflink idref="bib27" id="ref9">27</reflink>]; Poli & Agrimi, [<reflink idref="bib29" id="ref10">29</reflink>]; Ssenyonga et al., [<reflink idref="bib32" id="ref11">32</reflink>]; Torstveit et al., [<reflink idref="bib35" id="ref12">35</reflink>]), at least when no active parental consent is needed. Hence, school-based epidemiological research may be a valuable approach in countries in which the majority of adolescents and young adults are still attending school (e.g., in Switzerland; SBFI, [<reflink idref="bib31" id="ref13">31</reflink>]).</p> <p>However, the schools' unwillingness to participate might eventually turn into the pivotal barrier for reaching the students in the first place. To what degree this barrier actually poses a problem in school-based surveys is difficult to estimate, since a significant proportion of the published epidemiological research has been either based on convenience samples (e.g., Brener et al., [<reflink idref="bib2" id="ref14">2</reflink>]; Castrén et al., [<reflink idref="bib3" id="ref15">3</reflink>]) or – among those that used a random school sample – often has not (separately) reported response rates for schools (e.g., Mbulo, [<reflink idref="bib22" id="ref16">22</reflink>]; Sasmaz et al., [<reflink idref="bib30" id="ref17">30</reflink>]). Besides lacking knowledge on the response rates at the school level, the reasons why some schools decide not to participate have not been elaborated systematically with established qualitative methodological approaches. Hence, existing guides, while potentially providing helpful guidance on how to best conduct school-based surveys, lack a systematically established footing (Alibali & Nathan, [<reflink idref="bib1" id="ref18">1</reflink>]; Farringdon et al., [<reflink idref="bib11" id="ref19">11</reflink>]; Harrington et al., [<reflink idref="bib16" id="ref20">16</reflink>]; Vukotich et al., [<reflink idref="bib37" id="ref21">37</reflink>]). Systematically elaborating a more nuanced understanding of possible nonresponse biases could thus not only help to refine extant guides, but also to improve response rates at the school level in school-based surveys, for instance, by addressing possible concerns of school staff in a more effective and proactive manner. Such means will have to be implemented at an early stage of the recruitment, as the willingness of schools to participate is the initial step in any school-based survey, and thereby complement the already more thoroughly studied measures aimed at counteracting biases emerging at a later stage in the recruitment process (Wolfenden et al., [<reflink idref="bib38" id="ref22">38</reflink>]).</p> <p>Based on these research gaps, the present article used a mixed methods approach to 1) study factors that might be associated with non-participation at the school level, and 2) elaborate on how principals justify the decision for their school not to participate in a particular survey. The remainder of this article is structured as follows: Firstly, our case study – the '<emph>Swiss Youth Mental Health Literacy and Stigma Survey" (SYMHLSS)</emph> (including its two-stage sampling strategy) – is detailed. Secondly, predictors for the non-participation of schools are studied by means of logistic regression (quantitative analyses). Thirdly, modes of justifications for non-participation of schools are analysed using qualitative methods informed by grounded theory. Finally, the findings from the quantitative and qualitative analyses are integrated and the theoretical and practical implications are discussed.</p> <hd id="AN0156163090-3">Methods</hd> <p></p> <hd id="AN0156163090-4">The Swiss youth mental health literacy and stigma survey (SYMHLSS)</hd> <p></p> <hd id="AN0156163090-5">Background, content and ethics</hd> <p>The <emph>SYMHLSS</emph> was adapted from the Australian National Survey of Youth Mental Health Literacy and Stigma (Jorm et al., [<reflink idref="bib19" id="ref23">19</reflink>]; Wright et al., [<reflink idref="bib39" id="ref24">39</reflink>]). The aim of the study was to explore mental health literacy and stigmatizing attitudes towards different mental disorders in a representative population-based sample of young people. The study protocol has been approved by the ethics committee of the University of Zurich (approval number: 17.4.9).</p> <hd id="AN0156163090-6">Target population</hd> <p>A detailed description of the target population of the <emph>SYMHLSS</emph> can be found in the Supplementary Material 1. In short, the target population consisted of students on the upper-secondary education level (mostly between 15- and 20-years old) in the German-speaking part of Switzerland. After concluding mandatory school, students can generally follow one of two academic paths at this educational level: general education (GE) or vocational education and training (VET). The latter is the predominant form pursued by about two thirds of young people in Switzerland overall compared to about one fourth who are pursuing a GE track. In the German-speaking part of Switzerland, which marks the exclusive focus of the <emph>SYMHLSS</emph>, VET is even more common than in the other language regions.</p> <hd id="AN0156163090-7">Sampling strategy</hd> <p>A detailed description of the sampling strategy used for the <emph>SYMHLSS</emph> can be found in Supplementary Material 2. In short, a two-stage stratified sampling design was used to yield a representative sample of the student population in upper-secondary education in the German-speaking part of Switzerland. It aimed to reach a final sample of about 5,000 students. The first-stage sampling units consisted of individual public and private schools offering GE or VET at the upper-secondary level. These schools were sampled systematically from a comprehensive national list (school sampling frame). Schools were divided into two groups (explicit strata), based on whether they provide GE (strata I) or VET (strata II). The sample was allocated proportionally between these two strata. The second-stage sampling units were classes within schools (three classes per school were selected).</p> <hd id="AN0156163090-8">Contacting schools</hd> <p>All principals of the randomly selected schools were informed by email about the study and asked to participate. In some cantons, support from a relevant cantonal contact person (e.g., from the cantonal educational department) was provided in form of a letter that recommended schools to participate. This letter was attached to the information email. A reminder email was sent to those principals who did not respond to the first email within approximately two weeks. This reminder also included a motivational statement of how many schools already decided to participate. Principals who still did not respond to this reminder were additionally contacted by phone. Altogether, 180 schools were asked to participate (excluding ineligible schools, but including substitute schools that were contacted if the initially selected school decided not to participate), of which 105 participated (see Supplementary Material 2 for details).</p> <hd id="AN0156163090-9">Quantitative analyses: predictors for non-participation</hd> <p>Each school was either coded as participating (coded as 0; n = 105) or non-participating (coded as 1; n = 75; see Supplementary Material 2). Logistic regression analyses were used to examine the association between the following predictors and non-participation, whereby both crude and adjusted odds ratios (OR) were calculated:</p> <p></p> <ulist> <item> <emph>Support from a relevant cantonal contact person</emph>: not present (coded as 0) vs. present (coded as 1).</item> <p></p> <item> <emph>School ownership</emph>: public (coded as 0) vs. private (coded as 1).</item> <p></p> <item> <emph>School size</emph>: up to 1000 students (coded as 0) vs. more than 1000 students (coded as 1).</item> <p></p> <item> <emph>School type</emph>: GE (coded as 0) vs. VET (coded as 1).</item> </ulist> <hd id="AN0156163090-10">Qualitative analyses: justifications given for non-participation</hd> <p>The qualitative methods were used to deepen our rather rudimentary understanding (Crowe et al., [<reflink idref="bib6" id="ref25">6</reflink>]) of why schools reject the participation and how they justify their non-participation. More specifically, we sought to flesh out the core modes of justification from the schools' non-participation narratives (Czarniawska, [<reflink idref="bib8" id="ref26">8</reflink>]) in order to build a conceptual model of non-participation in school-based surveys. Of the 75 non-participating schools, seven were excluded from the qualitative analyses – either because they did not respond to our request with an official refusal (e.g., principals who could not be reached despite several attempts of making contact; n = 4) or because they did refuse but without justifying their decision (e.g., principals who only wrote that their school will not participate; n = 3). Hence, the principals' answers from the remaining 68 non-participating schools were considered for the qualitative analyses. Most of these answers were received via e-mails with a length of up to 180 words (n = 57). The first or second author received the remaining 11 answers from principals via phone and transcribed the content of the call for the analyses. No structured interview guide was used. Rather, the principals were asked to elaborate on the reasons for their non-participation decision, in order to still motivate them to participate in the study. These responses have been fed into MAXQDA ([<reflink idref="bib21" id="ref27">21</reflink>]), which is well-suited for a systematic analysis informed by grounded theory (Charmaz, [<reflink idref="bib4" id="ref28">4</reflink>]; Corbin & Strauss, [<reflink idref="bib5" id="ref29">5</reflink>]; Glaser & Strauss, [<reflink idref="bib14" id="ref30">14</reflink>]). Early line-by-line coding (i.e. in-vivo coding) consisted in labelling (e.g., identifiers of themes) close to data. Focused coding allowed grouping these initial codes into broader categories reflecting both their prevalence and analytical relevance. Theoretical coding allowed for further elaboration on the relationship between categories in favor of an overall theoretical model (Charmaz, [<reflink idref="bib4" id="ref31">4</reflink>]). This iterative process was continued until theoretical saturation within the given data set was achieved (Corbin & Strauss, [<reflink idref="bib5" id="ref32">5</reflink>]). Throughout the process, we used 'constant comparison' as our core analytical tool to iteratively move from data to theoretical model (Glaser & Strauss, [<reflink idref="bib14" id="ref33">14</reflink>]). Furthermore, we made extensive use of memos and drawing of diagrams for ideating, documenting, and reflecting on the process of theory development (Charmaz, [<reflink idref="bib4" id="ref34">4</reflink>]; Thornberg, [<reflink idref="bib33" id="ref35">33</reflink>]).</p> <hd id="AN0156163090-11">Results</hd> <p></p> <hd id="AN0156163090-12">Quantitative analyses: predictors for non-participating</hd> <p>Support from a relevant cantonal contact person was associated with a lower likelihood of non-participation, both in unadjusted and adjusted analyses (Table 1). Furthermore, smaller schools were (slightly) more likely not to participate compared to larger schools. In contrast, the ownership (public or private) and type of school (GE vs. VET) were not significantly associated with non-participation.ggg</p> <p>Table 1. Logistic regression models for non-participating in the Swiss youth mental health literacy and stigma survey, Switzerland 2017/2018</p> <p> <ephtml> <table><thead><tr><td /><td>Participation</td><td>Non-participation</td></tr><tr><td /><td><italic>n</italic> (%)</td><td><italic>n</italic> (%)</td><td /><td /></tr><tr><td>Total (<italic>n</italic> = 180)</td><td>105 (58.3)</td><td>75 (41.7)</td><td>Crude OR [CI]</td><td>Adjusted OR [CI]</td></tr></thead><tbody><tr><td><italic>Support from a relevant cantonal contact</italic> Not present Present</td><td>56 (49.1) 49 (74.2)</td><td>58 (50.9) 17 (25.8)</td><td>1.00 0.34 [0.17–0.65]***</td><td>1.00 0.33 [0.17–0.64]***</td></tr><tr><td><italic>Type of school</italic> Public Private</td><td>86 (58.9) 19 (55.9)</td><td>60 (41.1) 15 (44.1)</td><td>1.00 1.13 [0.53–2.40]</td><td>1.00 1.14 [0.50–2.59]</td></tr><tr><td><italic>School's ownership</italic> Up to 1000 students More than 1000 students</td><td>51 (51.5) 54 (66.7)</td><td>48 (48.5) 27 (33.3)</td><td>1.00 0.53 [0.29–0.98]*</td><td>1.00 0.53 [0.27–1.05]<sup>#</sup></td></tr><tr><td><italic>School type</italic> GE VET</td><td>25 (53.2) 80 (60.2)</td><td>22 (46.8) 53 (39.8)</td><td>1.00 0.75 [0.39–1.47]</td><td>1.00 0.94 [0.43–2.01]</td></tr></tbody></table> </ephtml> </p> <p>1 GE = general education; VET = vocational education and training; CI = 95% confidence interval; OR = odds ratio; # = p.10 (trend); * = p <.05; ** = p <.01; *** = p <.001</p> <hd id="AN0156163090-13">Qualitative analyses: justifications given for non-participation</hd> <p>Our analytical procedure revealed three types of modes of justification: thematic, attributional, and temporal. First, we found five <emph>thematic modes of justification</emph>, each one depicting one broader theme respondents used to justify their non-participation (see Table 2).</p> <p>Table 2. Five thematic modes of justifying non-participation in the Swiss youth mental health literacy and stigma survey, Switzerland 2017/2018 (ordered according to their frequency of being mentioned, from highest to lowest)</p> <p> <ephtml> <table><thead><tr><td>Thematic modes</td><td>Description</td><td>Translated example</td></tr></thead><tbody><tr><td><list list-type="Bullet"><list-item><p>(1) (Lack of) organizational resources</p></list-item></list></td><td>47.1% of the respondents mentioned limited organizational resources as a reason for non-participation, such as scarce financial resources or – most notably – a lack of time.</td><td><bold><italic>'</italic></bold><italic>With many special weeks, cancellations, inter-company teaching days etc. we are already severely limited in terms of lessons available. Therefore, we do not want to "sacrifice" any more time for surveys.'</italic></td></tr><tr><td><list list-type="Bullet"><list-item><p>(2) (Excessive) amount of study requests</p></list-item></list></td><td>41.2% of the respondents mentioned the number of study requests that the schools receive (also covering sub-themes such as an increasing or excessive amount of study requests) as a rationale for justifying their non-participation. In this connection, some principals also mentioned that they have recently completed, are currently involved in, or have already planned participation in other research projects.</td><td><bold><italic>'</italic></bold><italic>We are harassed with such study requests on a daily basis.'</italic></td></tr><tr><td><list list-type="Bullet"><list-item><p>(3) (Protection of) school's educational functions</p></list-item></list></td><td>39.7% of the respondents mentioned the need to protect the schools' educational functions – primarily composed of the sub-categories teaching and learning. This association substantiated that schools justify their non-participation to a large degree by framing the decision as a means for protecting their pupils' time for learning in a pre-structured curriculum and class schedule. This third thematic mode was strongly associated with the first one, i.e. 'lack of organizational resources' (16 schools mentioned both themes).</td><td><bold><italic>'</italic></bold><italic>Each survey takes time to complete, which is then missing for the actual subject teaching. Our students are only here one day a week. Hence, any loss of lessons is difficult to compensate.'</italic></td></tr><tr><td><list list-type="Bullet"><list-item><p>(4) (Protection of) school's administrative functions</p></list-item></list></td><td>To a less substantial degree (below 20%) of relevance was the protection of the school's administrative functions composed of sub-categories such as organizational restructuring or management succession.</td><td><bold><italic>'</italic></bold><italic>We will not participate in the survey due to a change in the management team; four members have left the school.'</italic></td></tr><tr><td><list list-type="Bullet"><list-item><p>(5) Embedding in institutional contexts</p></list-item></list></td><td>The embeddedness in the broader institutional contexts, such as the differing ownership structures (public versus private), was also relatively rarely mentioned (less than 20%).</td><td><bold><italic>'</italic></bold><italic>We are a private school and cannot simply use lessons, which are financed by the students, for other purposes.'</italic></td></tr></tbody></table> </ephtml> </p> <p>A more detailed analysis of the different usages and combinations of themes made us aware that while many non-participation narratives framed the school (e.g., teaching and learning) as the object in need of protection and increased stability, some of them attributed the epicentre of change and imminence either to the outside or the inside of the school. This second type of modes of justification, labelled as <emph>attributional modes of justification</emph>, thus consists of two distinct modes (see Table 3).</p> <p>Table 3. Two attributional modes of justifying non-participation in the Swiss youth mental health literacy and stigma survey, Switzerland 2017/2018</p> <p> <ephtml> <table><thead><tr><td>Attributional modes of justification</td><td>Description</td><td>Translated example</td></tr></thead><tbody><tr><td>Outside-in</td><td>The locus of change in the <italic>outside-in mode</italic> is attributed to (school) external forces, whereas the school's internal organization (e.g., its organizational resources) is portrayed as still being stable but eventually susceptible to these external forces (particularly the excessive amount of study requests). The non-participation is justified with the aim of maintaining the internal stability in favour of protecting the teaching and learning activities from external disturbances.</td><td><italic>'We are currently receiving many requests to participate in studies. Most of them are surveys that should be filled out by our students. In order to protect our students, we have decided not to take part in any studies for the time being.'</italic></td></tr><tr><td>Inside-out</td><td>The epicentre of change in the <italic>inside-out mode</italic> is attributed to the school itself, for example, in terms of a change in leadership. The refusal to participate is justified with the aim of protecting the school from any further external tasks in addition to the already unfolding internal challenges.</td><td><italic>'Our [name of school] is currently undergoing a major transformation process [...]. [I]n addition to the development of a new teaching culture by means of various training courses, we are also evaluating the entire implementation process and the concepts by means of several surveys of student and teachers [...]. A further survey would place an additional burden on our everyday school life.'</italic></td></tr></tbody></table> </ephtml> </p> <p>In the outside-in mode of justification, the locus of imminence was conceived to be external (in the school's environment) and predominantly connected to the theme '(excessive) amount of study requests' (see Table 2), whereas the school's internal organization (e.g., its organizational resources) was portrayed as still being stable but eventually susceptible to external forces. In this case, non-participation was justified with the aim of maintaining the internal stability in favour of protecting the teaching and learning activities from external disturbance. In contrast, the epicentre of change in the inside-out mode of justification was attributed to the school itself, for example, in terms of a change in leadership. In this case, the refusal to participate was based on the aim to protect the school from any further external tasks in addition to the already unfolding internal challenges.</p> <p>The third type of modes of justification pertains to the temporal constructions of the non-participation narratives. More specifically, we found two dominant <emph>temporal modes of justification</emph>, which differ in terms of the duration of the validity of a non-participation decision: an event-driven vs. strategy-based mode of justification (see Table 4).</p> <p>Table 4. Three temporal modes of justifying non-participation in the Swiss youth mental health literacy and stigma survey, Switzerland 2017/2018 (ordered according to the duration of the validity of a non-participation decision, from temporary to more stable)</p> <p> <ephtml> <table><thead><tr><td>Temporal modes of justification</td><td>Description</td><td>Translated example</td></tr></thead><tbody><tr><td>(1) Event-driven</td><td>A core characteristic of the event-driven mode was the (event-related) limited temporal validity of a decision. Hence, the same request for study participation might on another occasion have evoked a different (and thus positive) decision.</td><td>'<italic>Unfortunately, we just had to digest a death due to psychological reasons at our school, which in various respects has affected both teachers and students extraordinarily. Such a survey would stir up so much again that I could not answer for it'</italic></td></tr><tr><td>(2) Emergent</td><td>The <italic>emergent strategies</italic> mode is located in the space between the two dominant temporal modes of justification (event-driven and strategy-based). The common denominator of this mode consists in counteracting the perceived increase of requests by more generally curtailing study participations beyond simply rejecting the requests of the study at hand. Some schools still draw on an event-based narrative, while others already render it into a more generalized, strategy-based rationale.</td><td><italic>'Our vocational school and its departments are currently flooded with survey requests. We are therefore forced to make regulatory restrictions here and we will not participate in your project.'</italic><italic>'Over the past months we have participated in numerous research projects and surveys [...], as we have done in recent years. We are well aware of the importance of such surveys, but the executive board has decided that we will not participate in such activities in the coming months, which are not necessarily required by the [name of authority]. Our students and staff deserve to devote a few months to their core business.'</italic></td></tr><tr><td>(3) Strategy-based</td><td>The validity of the non-participation decision in the <italic>strategy-based</italic> mode was subject to more generalized characteristics and conditions. In its extreme form, this mode manifests itself in the school management's generalized decision to (radically) limit the number of study participations or even reject all future requests independent of the study's quality.</td><td><italic>'[We] do not doubt the usefulness of your investigation. Nevertheless, we refuse to participate. We receive daily requests to make students available for an empirical study. We cannot and do not wish to make the comparatively scarce teaching time in the Canton of [name of Canton] available for schoolexternal tasks. We only participate in surveys, which a) are initiated or ordered by the authorities of the Canton of [name of canton], b) we carry out ourselves as part of our quality system, or which c) are carried out by our own students as part of their high school diploma thesis.'</italic></td></tr></tbody></table> </ephtml> </p> <p> <emph>Event-driven</emph> decisions for non-participation were mainly anchored in events such as ongoing school reorganizations and evaluation projects, special learning vehicles (e.g., learning week), or dramatic incidents (e.g., suicide), – and most notably – a school's participation in other research projects. A core constitutive characteristic of the event-driven mode was thus the (event-related) limited temporal validity of a decision. Hence, the same request for study participation might on another occasion have evoked a different (thus positive) decision. In contrast, the validity of the non-participation decision in the <emph>strategy-based</emph> mode, rather than being related to a specific event and of short-term, was subject to more generalized characteristics and conditions. This strategy-based mode of justification was predominantly anchored in an ostensibly large number of requests for participating in research projects, which led to the school management's generalized decision to (radically) limit the number of study participations or even reject all future requests independent of the study's quality. Yet, the difference between event-driven and strategy-based rationales did not seem to be clear-cut. While some responses (n = 4) fully lacked the necessary indications for categorizing the refusal as either being event-driven or strategy-based (in these cases justifying their choice was exclusively based on resource restrictions), various responses (n = 9) provided evidence for a continuum-like space unfolding in-between the two dominant temporal modes of justification. These 11.8% not only mentioned a large but also an increasing amount of study requests as the main reason for (possibly) no longer participating in school-based surveys. Thus the common denominator of this third temporal mode of justification, a transition mode here labelled as '<emph>emergent strategies</emph>', consisted in counteracting the perceived increase of requests by more generally curtailing study participations beyond simply rejecting the requests of the study at hand – with some schools still rather drawing on an event-based narrative and others already rendering it into a more generalized, strategy-based rationale.</p> <p>Relating the qualitatively derived codes and modes of justification to the quantitative measures of non-participation allowed gaining additional tentative insights into the subject matter. More specifically, our data suggests that larger schools were more likely to draw on a strategy-based mode of justification, while smaller schools rather justified their decisions in an event-based manner. Furthermore, although we neither found a significant nor a substantial difference between the ownership of the school and the unwillingness of schools to participate in the survey, some principals of private schools explicitly mentioned that they could not justify to let students fill out the questionnaire during lessons, for which students actually had to pay for.</p> <hd id="AN0156163090-14">Discussion</hd> <p>The present article used a mixed methods approach to 1) study predictors for non-participation at the school level in an epidemiological survey (quantitative analyses) and 2) elaborate on the modes of justification in order to gain insights into why principals reject the participation and how they legitimize their decision (qualitative analyses). The quantitative analysis found that the odds of a school's non-participation were higher among smaller schools and if no support from a relevant contact person was present (e.g., a recommendation letter from cantonal authorities). The qualitative analysis identified the lack of organizational resources (especially a lack of time), the (increasing and excessive) number of study requests and the need to protect the educational functions of the schools (especially the pupils' time for learning) as the main themes for justifying a school's non-participation. The need to protect the educational functions was mentioned regardless of whether the school experienced changes which occurred externally (e.g., study requests from third parties) or internally (e.g., change of the school's management). Lastly, a temporal continuum of the validity of justification for non-participation was identified, ranging from event-driven (rather momentarily valid decisions) to emergent strategy-based and strategy-based decisions (more permanent decision that – at the extreme – implies a rejection of all study requests).</p> <p>Our qualitative results resonate with the sparse <emph>prior research in the field</emph> of mental health, since similar themes of justification have been found in previous studies. As such, our study further substantiates extant assumptions suggesting that schools refrain from participating due a lack of time and organizational resource (Torstveit et al., [<reflink idref="bib35" id="ref36">35</reflink>]) and thus to protect pupils' education, as well as due to a recent or current participation in other studies (Meilstrup et al., [<reflink idref="bib23" id="ref37">23</reflink>]; Torstveit et al., [<reflink idref="bib35" id="ref38">35</reflink>]) and thus to protect the school from additional tasks from the environment (also see Farringdon et al., [<reflink idref="bib11" id="ref39">11</reflink>]). However, when turning to the predictors of non-participation (quantitative analyses), we have to account for a Danish study (Meilstrup et al., [<reflink idref="bib23" id="ref40">23</reflink>]) which has found contradicting results to our study, suggesting that smaller instead of larger schools are more likely to participate in a research project. However, this discrepancy might be explained by the different survey methodologies. In contrast to the Danish study, our study did not survey <emph>all classes</emph> of particular grades within the randomly selected schools, but only three classes per school independent of school size. Hence, the relative effort for a school to participate was smaller for larger schools.</p> <p>The results of our analyses also resonate with long-standing theoretical traditions from the field of organization and management studies, particularly those anchored in the broader strands of contingency theory (Donaldson, [<reflink idref="bib10" id="ref41">10</reflink>]; Ginsberg & Venkatraman, [<reflink idref="bib13" id="ref42">13</reflink>]) – a theoretical approach, which has also gained notable attention in studies of school organizations more specifically (Hanson, [<reflink idref="bib15" id="ref43">15</reflink>]; Tyler, [<reflink idref="bib36" id="ref44">36</reflink>]). First, contingency theory largely focuses on how (objectively and subjectively experienced) environmental (e.g., velocity of environmental change) and organizational (e.g., size of organization) factors and associated uncertainties shape other organizational aspects (e.g., structures, strategies, performance). On the most general level, it thus helps us to explain that experienced changes in the environment (e.g., increasing study requests) or organization (e.g., organizational restructuring) have potential effects on how schools' decision-makers handle requests to participate in studies. Secondly, Mintzberg's (Mintzberg & McHugh, [<reflink idref="bib25" id="ref45">25</reflink>]) seminal work on organizational strategies inter alia shows that realized strategies, as patterned behaviour and decisions, are only partially intended, deliberate and explicitly pre-articulated but to varying degree 'emergent' and thus 'realized despite or in the absence of intentions' – inter alia depending on the type of organization and environment (Mintzberg & Waters, [<reflink idref="bib26" id="ref46">26</reflink>]). His work thus provides a potential framework to explain the temporal modes of justifications, namely how repeated event-driven decisions to reject study requests might increasingly emerge into a strategy-based and thus generalized decision when such requests are surging. Thirdly, contingency theoretical approaches (e.g., Mintzberg, [<reflink idref="bib24" id="ref47">24</reflink>]) support the argument that the administrative division of larger schools is functionally more differentiated into task-specific departments (e.g., matching the environmental complexity and higher amount of requests) and prepared to handle such study requests in a routinized and formalized manner (e.g., pre-evaluation, communication), whereas in smaller schools, such tasks are administratively directly handled by the principals themselves. This explains why larger schools rather draw on a strategy-based mode of justification, while for smaller schools this is more likely to be event-driven (see also Mintzberg & Waters, [<reflink idref="bib26" id="ref48">26</reflink>]). Hence, contingency theory enables us to formulate the broader <emph>theoretical implications</emph> of our findings by integrating them into a coherent conceptual framework for future studies seeking to explain non-participation of schools in school-based surveys.</p> <p>The present study also has <emph>methodological implications</emph> concerning the sampling strategy and the motivational tactics for persuading the schools to participate in the study. Firstly, school size has to be considered in the sampling strategy if subsequent studies confirm that larger schools are more likely to participate than smaller ones and in case that school size is assumed to be associated with relevant study variables (especially with the target outcome). In our study, substitute schools were similar to initially selected schools in terms of school size, since school size was used in the implicit stratification. In other words, the way substitute schools were determined was adequate to replace non-participating small schools. An oversampling of small schools and an under-sampling of larger schools could be considered alternatively or additionally. However, it would have to be determined in more detail where to draw the cut-off between small vs. large schools. Furthermore, the trade-off of this over-/under-sampling approach must be considered, i.e. varying survey weights for small and large schools, which leads to less precise population estimates. The advantage of an oversampling of small schools could, however, consist in allowing subgroup-analyses (n of small schools would be large enough). In addition, if school size proves to be relevant for non-response at the school level, it would be necessary to incorporate school size into the non-response adjustment for survey weights. A second methodological implication pertains to schools enacting a strategy-based mode of justification, which barely leaves room for motivational tactics (see above) to persuade a school to suddenly reassess its otherwise fairly generalized decision not to participate. Our analysis suggests that installing an institutional gatekeeper (Hirsch, [<reflink idref="bib17" id="ref49">17</reflink>]) who endorses a study might be the most effective mitigation strategy to reduce uncertainty on the side of the researchers and schools and to increase the likelihood of participation (see also e.g., Farringdon et al., [<reflink idref="bib11" id="ref50">11</reflink>]; Harrington et al., [<reflink idref="bib16" id="ref51">16</reflink>]; Vukotich et al., [<reflink idref="bib37" id="ref52">37</reflink>]). Such a gatekeeper-based mitigation strategy might be particularly relevant for larger schools, since they are more likely to draw on a strategy-based mode of justification. Thirdly, however, once the schools have been contacted, the non-response rate at the school level can particularly be reduced by focusing additional motivational efforts on schools drawing on an event-based mode of justification, since the reason for their refusal is mostly not anchored in the specific study but rather in the current resources available. Planning the necessary temporal flexibility for the participation of the schools might thereby help to increase the response rate.</p> <p>The <emph>practical implications</emph> of the present study concern the potential coordination and regulation of future school-based surveys. The large amount of study requests and the respective participation in such research projects was one of the core rationales for declining the participation in the study. The concept of emerging strategies alerts us that schools tend to eventually counteract a surging number of requests for study participation by a priori declining any future requests independent of the quality of the study. This points to the risk that those often publicly funded studies focusing on building the pivotal insights for improving school-related activities and conditions (e.g., to improve pupils' health) are denied access for collecting the data. Hence, it might be of public interest to launch a dialogue between schools and scholars to better coordinate future school-based research agendas and quality standards (e.g., with a joint regional survey coordination system).</p> <p>Although the present study offers original insights into the (non-)participation of schools, the following <emph>limitations</emph> have to be taken into account. First, our analyses were solely built on data from the <emph>SYMHLSS</emph>. Even though some of the findings were in line with previous research, it needs to be further tested whether and to what extent the results of the current study are also valid for studies focusing on other topics, featuring other target populations (e.g., students attending mandatory schools), or being conducted in other cultural-geographic contexts. Additional lessons learnt from other researchers on effective recruitment and retention strategies for schools should also be considered when a school-based research project is being planned (e.g., approaching schools before their yearly strategic planning in order to maximize their ability and willingness to incorporate new research projects in their schedule) (Alibali & Nathan, [<reflink idref="bib1" id="ref53">1</reflink>]; Farringdon et al., [<reflink idref="bib11" id="ref54">11</reflink>]; Vukotich et al., [<reflink idref="bib37" id="ref55">37</reflink>]). Secondly, it must be considered that if the initially selected school refused to participate a <emph>similar</emph> substitute school was – if available – contacted. Hence, two data points on similar schools were available for the analyses. In contrast, if the initially selected school agreed to participate, only one data point was present. However, similar results were obtained in additional analyses that only allowed use of one data point (results not shown). Thirdly, we only conducted post hoc analyses of predictors and modes of justifications of non-participating schools. Fourthly, it has to be kept in mind that we barely found any evidence of non-response bias. However, a more detailed analysis (e.g., based on in-depth interviews) might possibly point to such biases. Lastly, it must be kept in mind that the data collection took place before the COVID-19 pandemic and its substantial impact on the everyday school life in Switzerland. Pandemics and other incidents that lead to lockdowns may represent an additional challenge for future school-based surveys.</p> <hd id="AN0156163090-15">Conclusions</hd> <p>When targeting adolescents and young people in the general population (e.g., in epidemiological research), school-based surveys are – at least for the time being – an effective approach to countervail the declining response rates which affect other survey methods, at least when schools are not locked down (e.g., due to a pandemic). However, while school-based surveys are characterized by low refusal rates at the student level (including the SYMHLSS; Dey et al., [<reflink idref="bib9" id="ref56">9</reflink>]), the present study suggests that a major challenge for school-based epidemiological surveys increasingly consists in the high refusal rates at the school level. However, rather than necessarily being associated with worrisome response biases (e.g., Thrul et al., [<reflink idref="bib34" id="ref57">34</reflink>]), our study showed that schools can become a problematic bottleneck for school-based surveys as they not only hold the power to reject requests for study participation, but increasingly do so exactly irrespective of the topic and quality of the actual study – and thus might increasingly impede the possibility of achieving representativeness in studies of young people. That is not to say that potential response biases no longer have to be carefully monitored in future studies. Scholars seeking to optimize the participation rate at the school level are also advised to involve institutional gatekeepers for endorsing the study prior to contacting the schools and to offer schools a flexible time frame for participation since these factors have been shown to increase the willingness to participate (also see: Alibali & Nathan, [<reflink idref="bib1" id="ref58">1</reflink>]; Farringdon et al., [<reflink idref="bib11" id="ref59">11</reflink>]). And furthermore, it might be fruitful to launch a dialogue between schools and scholars for coordinating the cooperation concerning future research projects. These efforts might be crucial to ensure the possibility for collecting representative data on young people in order to build the necessary scientific foundation for improving (e.g., school-related aspects of) their lives on the longer run.</p> <hd id="AN0156163090-16">Supplemental data</hd> <p>Supplemental data for this article can be accessed https://doi.org/10.1080/13645579.2020.1864088</p> <hd id="AN0156163090-17">Disclosure statement</hd> <p>No conflict of interest</p> <ref id="AN0156163090-18"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref18" type="bt">1</bibl> <bibtext> These authors contributed equally to this work.</bibtext> </blist> </ref> <ref id="AN0156163090-19"> <title> References </title> <blist> <bibtext> Alibali, M. W., & Nathan, M. J. (2010). Conducting research in schools: A practical guide. 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MJA, 183 (1), 18 – 23. https://doi.org/10.5694/j.1326-5377.2005.tb06881.x</bibtext> </blist> </ref> <aug> <p>By Michelle Dey; Laurent Marti; Laura Alexandra Helbling and Anthony Francis Jorm</p> <p>Reported by Author; Author; Author; Author</p> <p></p> <p>Michelle Dey , PhD, works at the Swiss Research Institute for Public Health and Addiction at the University of Zurich. Her research focuses on social epidemiology and mental health (in particular on mental health literacy and stigma). She is the PI of the 'Swiss Youth Mental Health Literacy and Stigma Survey', i.e. the survey that was used for the current article.</p> <p>Laurent Marti , MA, is a PhD student at the Yunus Centre for Social Business and Health, Glasgow Caledonian University, UK, and a project collaborator at the Swiss Research Institute for Public Health and Addiction, University of Zurich, Switzerland. His research focuses on organizational phenomena in various sectors, such as the mental health and third sector as well as the digital economy. He is the deputy PI of the 'Swiss Youth Mental Health Literacy and Stigma Survey'.</p> <p>Laura Alexandra Helbling , PhD, works at the Institute for Educational Evaluation at the University of Zurich with a focus on research in the field of educational transitions, academic performance development and learning analytics. She was responsible for the survey sampling of schools and students as basis for the current article.</p> <p>Anthony Francis Jorm , PhD, DSc, is an Emeritus Professor and NHMRC Leadership Fellow at the University of Melbourne, Australia. His research focuses on building community capacity for prevention and early intervention with mental disorders. He is a PT on the 'Swiss Youth Health Literacy and Stigma Survey'.</p> </aug> <nolink nlid="nl1" bibid="bib12" firstref="ref2"></nolink> <nolink nlid="nl2" bibid="bib28" firstref="ref3"></nolink> <nolink nlid="nl3" bibid="bib18" firstref="ref7"></nolink> <nolink nlid="nl4" bibid="bib20" firstref="ref8"></nolink> <nolink nlid="nl5" bibid="bib27" firstref="ref9"></nolink> <nolink nlid="nl6" bibid="bib29" firstref="ref10"></nolink> <nolink nlid="nl7" bibid="bib32" firstref="ref11"></nolink> <nolink nlid="nl8" bibid="bib35" firstref="ref12"></nolink> <nolink nlid="nl9" bibid="bib31" firstref="ref13"></nolink> <nolink nlid="nl10" bibid="bib22" firstref="ref16"></nolink> <nolink nlid="nl11" bibid="bib30" firstref="ref17"></nolink> <nolink nlid="nl12" bibid="bib11" firstref="ref19"></nolink> <nolink nlid="nl13" bibid="bib16" firstref="ref20"></nolink> <nolink nlid="nl14" bibid="bib37" firstref="ref21"></nolink> <nolink nlid="nl15" bibid="bib38" firstref="ref22"></nolink> <nolink nlid="nl16" bibid="bib19" firstref="ref23"></nolink> <nolink nlid="nl17" bibid="bib39" firstref="ref24"></nolink> <nolink nlid="nl18" bibid="bib21" firstref="ref27"></nolink> <nolink nlid="nl19" bibid="bib14" firstref="ref30"></nolink> <nolink nlid="nl20" bibid="bib33" firstref="ref35"></nolink> <nolink nlid="nl21" bibid="bib23" firstref="ref37"></nolink> <nolink nlid="nl22" bibid="bib10" firstref="ref41"></nolink> <nolink nlid="nl23" bibid="bib13" firstref="ref42"></nolink> <nolink nlid="nl24" bibid="bib15" firstref="ref43"></nolink> <nolink nlid="nl25" bibid="bib36" firstref="ref44"></nolink> <nolink nlid="nl26" bibid="bib25" firstref="ref45"></nolink> <nolink nlid="nl27" bibid="bib26" firstref="ref46"></nolink> <nolink nlid="nl28" bibid="bib24" firstref="ref47"></nolink> <nolink nlid="nl29" bibid="bib17" firstref="ref49"></nolink> <nolink nlid="nl30" bibid="bib34" firstref="ref57"></nolink>
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  Data: Non-Participation in Epidemiological School-Based Surveys: Using Mixed Methods to Study Predictors and Modes of Justification for (Non-)Participation at the School Level
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  Data: English
– Name: Author
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  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Dey%2C+Michelle%22">Dey, Michelle</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-4300-1877">0000-0002-4300-1877</externalLink>)<br /><searchLink fieldCode="AR" term="%22Marti%2C+Laurent%22">Marti, Laurent</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-9690-3727">0000-0002-9690-3727</externalLink>)<br /><searchLink fieldCode="AR" term="%22Helbling%2C+Laura+Alexandra%22">Helbling, Laura Alexandra</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-8310-5427">0000-0002-8310-5427</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jorm%2C+Anthony+Francis%22">Jorm, Anthony Francis</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-1424-4116">0000-0002-1424-4116</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22International+Journal+of+Social+Research+Methodology%22"><i>International Journal of Social Research Methodology</i></searchLink>. 2022 25(2):171-182.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: Y
– Name: Pages
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  Data: 12
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  Label: Publication Date
  Group: Date
  Data: 2022
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  Data: Journal Articles<br />Reports - Research
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Response+Rates+%28Questionnaires%29%22">Response Rates (Questionnaires)</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Surveys%22">Student Surveys</searchLink><br /><searchLink fieldCode="DE" term="%22Epidemiology%22">Epidemiology</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Principals%22">Principals</searchLink><br /><searchLink fieldCode="DE" term="%22Participation%22">Participation</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
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  Label: Geographic Terms
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  Data: <searchLink fieldCode="DE" term="%22Switzerland%22">Switzerland</searchLink>
– Name: DOI
  Label: DOI
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  Data: 10.1080/13645579.2020.1864088
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1364-5579
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Response rates in epidemiological studies have generally been decreasing over the past decades. However, when the target group consists of adolescents and young adults, school-based surveys have hitherto been able to mitigate this problem: This age group can be reached relatively easy in the school context (e.g., as compared to reaching them by phone) with very low refusal rates at the student level. However, the present study used a mixed-methods approach and suggests that schools at the organizational level have meanwhile become the problematic bottleneck for school-based surveys, as they increasingly reject requests for study participation. The current article provides insights into promising means for counteracting this trend. Researchers are advised to offer flexible timeframes for schools' participation and to involve institutional gatekeepers who are endorsing their study. Furthermore, researchers, funding agencies, and schools would benefit from joint regional survey coordination systems. Such means will be crucial for the representativeness of future school-based epidemiological surveys.
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  Data: 2022
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  Data: EJ1341490
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        StartPage: 171
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      – SubjectFull: Response Rates (Questionnaires)
        Type: general
      – SubjectFull: Student Surveys
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      – TitleFull: Non-Participation in Epidemiological School-Based Surveys: Using Mixed Methods to Study Predictors and Modes of Justification for (Non-)Participation at the School Level
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