{"doi":"10.1093/pm/pnae010","title":"Texting as a method to collect post-discharge data after major pediatric surgery: lessons learned","abstract":"The first weeks at home after a major pediatric surgery are critical for recovery and long-term prognosis.1 Despite this, we know little about the pain experienced during the early post-discharge period.2 A better understanding of recovery during this time could provide insight into factors associated with the development of adverse outcomes (eg, chronic post-surgical pain) and highlight intervention opportunities. Regarding remote data collection, it is critical that research teams collect both accurate and complete data. Furthermore, because the time following discharge is stressful to families, data collection should occur with the least amount of burden possible.4 While some studies have reported on outcomes such as pain and function post-discharge, no single method stands out as feasible, acceptable, and non-intrusive. In addition, assessment methods, timelines, and outcomes have varied considerably across studies, making it difficult to draw conclusions about methodology.3,5,6 Currently, it is difficult to know which methods provide the most complete and accurate data, and which are the least burdensome to the family and the research team. The study reported here, details our experience and lessons learned from the use of texting + Qualtrics (an online platform) to collect data from pediatric patients and parents during the first two weeks at home after a major surgery. The primary aim was to examine the method feasibility and acceptability. Secondary aims were to explore patient age and sex as factors that may influence data accuracy, in turn, negatively influencing feasibility. We hypothesized that the texting platform would be feasible and acceptable for patients and parents. No a priori hypotheses were specified for the analyses associated with the secondary aims.","journal":"Pain Medicine","year":2024,"id":494520,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9561,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":368741,"name":"Pippa Simpson","orcid":"0000-0003-1458-3748","position":1,"is_corresponding":false},{"id":1087863,"name":"W. Hobart Davies","orcid":"0000-0002-2531-1708","position":2,"is_corresponding":false},{"id":1341032,"name":"Han Joo Lee","orcid":"0000-0002-0085-8467","position":3,"is_corresponding":false},{"id":1341033,"name":"Chasity Brimeyer","orcid":"0000-0003-2960-6754","position":4,"is_corresponding":false},{"id":1341271,"name":"Michelle L. Czarnecki","orcid":null,"position":5,"is_corresponding":false},{"id":1341272,"name":"Brynn LiaBraaten","orcid":null,"position":6,"is_corresponding":false},{"id":1341273,"name":"Gabriella Mauro","orcid":null,"position":7,"is_corresponding":false},{"id":911072,"name":"Steven J. Weisman","orcid":"0000-0001-7780-0725","position":8,"is_corresponding":false},{"id":911073,"name":"Keri R. Hainsworth","orcid":"0000-0002-1203-0157","position":9,"is_corresponding":false},{"id":1341031,"name":"Ashin Mehta","orcid":"0000-0001-5757-4636","position":0,"is_corresponding":true}],"reference_count":11,"raw_metadata":null,"created_at":"2026-07-19T02:09:11.736910Z","pmid":"38377400","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}