{"id":"https://openalex.org/W2602970604","doi":null,"title":"Dropouts on the web: Effects of interest and burden experienced during an online survey","display_name":"Dropouts on the web: Effects of interest and burden experienced during an online survey","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2602970604","mag":"2602970604"},"language":"en","primary_location":{"id":"mag:2602970604","doi":null,"is_oa":false,"landing_page_url":"https://www.irss.unc.edu/content/pdf/Dropouts%20Galesic%20JOS%202006.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S13624874","display_name":"Quality Engineering","issn_l":"0898-2112","issn":["0898-2112","1532-4222"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-c","jufo-1","ki-jl-1","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Quality Engineering","raw_type":null},"volume":null,"type":"article","indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071165387","display_name":"Mirta Gale\u0161i\u0107","orcid":"https://orcid.org/0000-0002-1712-9455","observed_orcids":["https://orcid.org/0000-0002-1712-9455"]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mirta Gale\u0161i\u0107","raw_affiliation_strings":["University of Maryland - College Park"],"raw_orcid":"https://orcid.org/0000-0002-1712-9455","affiliations":[{"raw_affiliation_string":"University of Maryland - College Park","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5071165387"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":2.2507,"has_fulltext":false,"cited_by_count":99,"citation_normalized_percentile":{"value":0.92633493,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"52","issue":"6","first_page":"617","last_page":"618"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11539","display_name":"Survey Methodology and Nonresponse","score":1.0,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11539","display_name":"Survey Methodology and Nonresponse","score":1.0,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13030","display_name":"Survey Sampling and Estimation Techniques","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/decision-field-theory","display_name":"decision field theory","score":0.7799999713897705},{"id":"https://openalex.org/keywords/survey-response-behavior","display_name":"survey response behavior","score":0.6069999933242798},{"id":"https://openalex.org/keywords/survey-design","display_name":"survey design","score":0.4050000011920929},{"id":"https://openalex.org/keywords/answer-quality","display_name":"answer quality","score":0.6600000262260437},{"id":"https://openalex.org/keywords/online-surveys","display_name":"online surveys","score":0.30399999022483826}],"concepts":[{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.7254919409751892},{"id":"https://openalex.org/C2984949393","wikidata":"https://www.wikidata.org/wiki/Q1260241","display_name":"Drop out","level":2,"score":0.7117587327957153},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.5602636933326721},{"id":"https://openalex.org/C173481278","wikidata":"https://www.wikidata.org/wiki/Q7257997","display_name":"Survey research","level":2,"score":0.5431976914405823},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.5419579148292542},{"id":"https://openalex.org/C198477413","wikidata":"https://www.wikidata.org/wiki/Q7647069","display_name":"Survey data collection","level":2,"score":0.5357545614242554},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.46254274249076843},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.43362027406692505},{"id":"https://openalex.org/C73945780","wikidata":"https://www.wikidata.org/wiki/Q814232","display_name":"Survey methodology","level":2,"score":0.41333746910095215},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4110827147960663},{"id":"https://openalex.org/C75630572","wikidata":"https://www.wikidata.org/wiki/Q538904","display_name":"Applied psychology","level":1,"score":0.3421311378479004},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.32177937030792236},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2292976677417755},{"id":"https://openalex.org/C4249254","wikidata":"https://www.wikidata.org/wiki/Q3044431","display_name":"Demographic economics","level":1,"score":0.1859757900238037},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.17451149225234985},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.14520519971847534},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10944083333015442},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10664263367652893},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.07596004009246826},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2602970604","doi":null,"is_oa":false,"landing_page_url":"https://www.irss.unc.edu/content/pdf/Dropouts%20Galesic%20JOS%202006.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S13624874","display_name":"Quality Engineering","issn_l":"0898-2112","issn":["0898-2112","1532-4222"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","dongbi-c","jufo-1","ki-jl-1","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"Quality Engineering","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[{"display_name":"Observational Study","id":"https://openalex.org/study-designs/observational-study"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W41087924","https://openalex.org/W151613567","https://openalex.org/W873683380","https://openalex.org/W1963846010","https://openalex.org/W1978871724","https://openalex.org/W1989473809","https://openalex.org/W1992123715","https://openalex.org/W1993679986","https://openalex.org/W2001498147","https://openalex.org/W2009292571","https://openalex.org/W2022730011","https://openalex.org/W2033606685","https://openalex.org/W2038108416","https://openalex.org/W2042813366","https://openalex.org/W2071384575","https://openalex.org/W2080273348","https://openalex.org/W2082905407","https://openalex.org/W2094244305","https://openalex.org/W2134032236","https://openalex.org/W2138534101","https://openalex.org/W2145388932","https://openalex.org/W2153605704","https://openalex.org/W2160947404","https://openalex.org/W2324392187"],"related_works":["https://openalex.org/W1502950997","https://openalex.org/W2182736527","https://openalex.org/W3172340302","https://openalex.org/W2554658613","https://openalex.org/W4230178573","https://openalex.org/W2099548776","https://openalex.org/W7099235674","https://openalex.org/W4310766499","https://openalex.org/W7098519659","https://openalex.org/W137293484"],"abstract_inverted_index":{"Dropouts":[0],"can":[1,110],"be":[2,111],"a":[3,23,41],"significant":[4],"problem":[5,15],"in":[6,40,113,130],"web":[7,42],"surveys,":[8],"but":[9],"theoretically":[10],"motivated":[11],"studies":[12],"of":[13,26,38,61,82,117,124,140],"this":[14,19],"are":[16],"rare.":[17],"In":[18],"study,":[20],"we":[21,53],"use":[22],"dynamic":[24],"theory":[25],"decision":[27,30,63],"making,":[28],"the":[29,51,77,101,114,122],"field":[31],"theory,":[32],"to":[33,64,137],"predict":[34],"and":[35,59,72,85,96,133],"explain":[36],"behavior":[37],"respondents":[39,102],"survey.":[43],"By":[44],"registering":[45],"respondents\u2019":[46,62],"momentary":[47],"subjective":[48],"experiences":[49],"throughout":[50,76],"survey,":[52,78],"gained":[54],"some":[55],"insights":[56],"into":[57],"antecedents":[58],"consequences":[60],"drop":[65,90],"out.":[66],"The":[67,126],"results":[68,127],"show":[69],"that":[70],"interest":[71,95],"experienced":[73,98],"burden":[74,99],"change":[75],"depending":[79],"on":[80],"characteristics":[81],"questions,":[83],"respondents,":[84],"survey":[86,141],"design.":[87],"Respondents":[88],"who":[89,103],"out":[91],"often":[92],"express":[93],"lower":[94],"higher":[97],"than":[100],"stay.":[104],"Their":[105],"growing":[106],"preference":[107],"for":[108],"dropout":[109],"detected":[112],"decreased":[115],"quality":[116],"their":[118],"answers":[119],"even":[120],"before":[121],"point":[123],"dropout.":[125],"could":[128],"help":[129],"practical":[131],"work":[132],"open":[134],"new":[135],"paths":[136],"theoretical":[138],"explanations":[139],"behavior.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2017-04-07T00:00:00"}