{"doi":"10.1002/aur.2833","title":"Using percentiles in the interpretation of Patient‐Reported Outcomes Measurement Information System scores: Guidelines for autism","abstract":"The objectives of this study were to (1) demonstrate the application of percentiles to advance the interpretation of patient-reported outcomes and (2) establish autism-specific percentiles for four Patient-Reported Outcomes Measurement Information System (PROMIS) measures. PROMIS measures were completed by parents of autistic children and adolescents ages 5-17 years as part of two studies (n = 939 parents in the first study and n = 406 parents in the second study). Data from the first study were used to develop autism-specific percentiles for PROMIS parent-proxy sleep disturbance, sleep-related impairment, fatigue, and anxiety. Previously established United States general population percentiles were applied to interpret PROMIS scores in both studies. Results of logistic regression models showed that parent-reported material hardship was associated with scoring in the moderate-severe range (defined as ≥75th percentile in the general population) on all four PROMIS measures (odds ratios 1.7-2.2). In the second study, the percentage of children with severe scores (defined as ≥95th percentile in the general population) was 30% for anxiety, 25% for sleep disturbance, and 17% for sleep-related impairment, indicating a high burden of these problems among autistic children. Few children had scores at or above the autism-specific 95th percentile on these measures (3%-4%), indicating that their scores were similar to other autistic children. The general population and condition-specific percentiles provide two complementary reference points to aid interpretation of PROMIS scores, including corresponding severity categories that are comparable across different PROMIS measures.","journal":"Autism Research","year":2022,"id":294004,"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":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9148,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":739629,"name":"Elizabeth A. Kaplan‐Kahn","orcid":"0000-0002-2481-3247","position":1,"is_corresponding":false},{"id":520804,"name":"Adam C. Carle","orcid":"0000-0002-3552-6534","position":2,"is_corresponding":false},{"id":979002,"name":"Laura Graham Holmes","orcid":"0000-0001-9928-6798","position":3,"is_corresponding":false},{"id":979003,"name":"Kiely Law","orcid":"0000-0003-2188-6106","position":4,"is_corresponding":false},{"id":316959,"name":"Judith S. Miller","orcid":"0000-0002-0796-0923","position":5,"is_corresponding":false},{"id":406525,"name":"Julia Parish‐Morris","orcid":"0000-0001-9633-2904","position":6,"is_corresponding":false},{"id":302148,"name":"Christopher B. Forrest","orcid":"0000-0003-1252-068X","position":7,"is_corresponding":false},{"id":381553,"name":"Julia Schuchard","orcid":"0000-0002-8613-8961","position":0,"is_corresponding":true}],"reference_count":49,"raw_metadata":null,"created_at":"2026-07-19T00:30:57.469517Z","pmid":"36259546","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":[]}